Phenomic, convergent functional genomic, and biomarker studies in a stress-reactive genetic animal model of bipolar disorder and co-morbid alcoholism

Temporal effects on death by suicide: empirical evidence and possible molecular correlates

Popular culture and medical lore have long postulated a connection between full moon and exacerbations of psychiatric disorders. We wanted to empirically analyze the hypothesis that suicides are increased during the period around full moons. We analyzed pre-COVID suicides from the Marion County Coroner's Office (n = 776), and show that deaths by suicide are significantly increased during the week of the full moon (p = 0.037), with older individuals (age ≥ 55) showing a stronger effect (p = 0.019). We also examined in our dataset which hour of the day (3-4 pm, p = 0.035), and which month of the year (September, p = 0.09) show the most deaths by suicide. We had blood samples on a subset of the subjects (n = 45), which enabled us to look at possible molecular mechanisms. We tested a list of top blood biomarkers for suicidality (n = 154) from previous studies of ours 7, to assess which of them are predictive. The biomarkers for suicidality that are predictive of death by suicide during full moon, peak hour of day, and peak month of year, respectively, compared to outside of those periods, appear to be enriched in circadian clock genes. For full moon it is AHCYL2, ACSM3, AK2, and RBM3. For peak hour it is GSK3B, AK2, and PRKCB. For peak month it is TBL1XR1 and PRKCI. Half of these genes are modulated in expression by lithium and by valproate in opposite direction to suicidality, and all of them are modulated by depression and alcohol in the same direction as suicidality. These data suggest that there are temporal effects on suicidality, possibly mediated by biological clocks, pointing to changes in ambient light (timing and intensity) as a therapeutically addressable target to decrease suicidality, that can be coupled with psychiatric pharmacological and addiction treatment preventive interventions.

Eosinophils to Lymphocytes Ratio (ELR) as a Potential Inflammatory Biomarker in Patients with Dual Diagnosis of Bipolar and Alcohol Use Disorders: A Retrospective Cohort Study

Objective: It is well-established that Bipolar Disorder (BD) has comorbidity with Alcohol Use Disorder (AUD) and could present the same symptoms of an underlying diagnosis of BD, therefore delaying the proper relevant treatment. Recent studies show the occurrence of alterations in the circulating levels of inflammatory mediators in patients dealing with AUD as well as those with BD. The objective of this study is to get an assessment of whether patients with AUD and BD comorbidity [BD(+)] would present different ratios of the Complete Blood Count (CBC) in comparison with patients with AUD but without a BD comorbidity [BD(-)]. Methods: This is a retrospective study, conducted through a selection of patients files who were admitted to the psychiatric department at Hôtel-Dieu de France University Hospital in Beirut, Lebanon, between January of the year 2016 and May of the year 2021. Overall, 83 files of patients dealing with AUD were included in this study. Results: Patients with BD(+) showed a higher Eosinophils to Lymphocytes Ratio (ELR) in comparison to those with BD(-). The Receiver Operation Characteristic (ROC) analysis had an area under the curve at 0.719 with a p = .001. The cutoff value of ELR that best differentiates BD(-) from BD(+) was 0.087 (Sensitivity = 81.3%; Specificity = 63.6%). The logistic regression analysis showed that an ELR superior to 0.087 presented a statistically significant difference, exposing patients belonging to the BD(+) group (OR = 11.66; p < .001). Conclusions: Our data suggest that ELR may be a valuable, reproducible, easily accessible, and cost-effective inflammatory marker, pointing at the presence of a BD comorbidity with AUD.

Neurobiological and behavioral mechanisms of circadian rhythm disruption in bipolar disorder: A critical multi-disciplinary literature review and agenda for future research from the ISBD task force on chronobiology

AIM

Symptoms of bipolar disorder (BD) include changes in mood, activity, energy, sleep, and appetite. Since many of these processes are regulated by circadian function, circadian rhythm disturbance has been examined as a biological feature underlying BD. The International Society for Bipolar Disorders Chronobiology Task Force (CTF) was commissioned to review evidence for neurobiological and behavioral mechanisms pertinent to BD.

METHOD

Drawing upon expertise in animal models, biomarkers, physiology, and behavior, CTF analyzed the relevant cross-disciplinary literature to precisely frame the discussion around circadian rhythm disruption in BD, highlight key findings, and for the first time integrate findings across levels of analysis to develop an internally consistent, coherent theoretical framework.

RESULTS

Evidence from multiple sources implicates the circadian system in mood regulation, with corresponding associations with BD diagnoses and mood-related traits reported across genetic, cellular, physiological, and behavioral domains. However, circadian disruption does not appear to be specific to BD and is present across a variety of high-risk, prodromal, and syndromic psychiatric disorders. Substantial variability and ambiguity among the definitions, concepts and assumptions underlying the research have limited replication and the emergence of consensus findings.

CONCLUSIONS

Future research in circadian rhythms and its role in BD is warranted. Well-powered studies that carefully define associations between BD-related and chronobiologically-related constructs, and integrate across levels of analysis will be most illuminating.

Enlightened: addressing circadian and seasonal changes in photoperiod in animal models of bipolar disorder

Bipolar disorders (BDs) exhibit high heritability and symptoms typically first occur during late adolescence or early adulthood. Affected individuals may experience alternating bouts of mania/hypomania and depression, with euthymic periods of varying lengths interspersed between these extremes of mood. Clinical research studies have consistently demonstrated that BD patients have disturbances in circadian and seasonal rhythms, even when they are free of symptoms. In addition, some BD patients display seasonal patterns in the occurrence of manic/hypomanic and depressive episodes as well as the time of year when symptoms initially occur. Finally, the age of onset of BD symptoms is strongly influenced by the distance one lives from the equator. With few exceptions, animal models useful in the study of BD have not capitalized on these clinical findings regarding seasonal patterns in BD to explore molecular mechanisms associated with the expression of mania- and depression-like behaviors in laboratory animals. In particular, animal models would be especially useful in studying how rates of change in photoperiod that occur during early spring and fall interact with risk genes to increase the occurrence of mania- and depression-like phenotypes, respectively. Another unanswered question relates to the ways in which seasonally relevant changes in photoperiod affect responses to acute and chronic stressors in animal models. Going forward, we suggest ways in which translational research with animal models of BD could be strengthened through carefully controlled manipulations of photoperiod to enhance our understanding of mechanisms underlying seasonal patterns of BD symptoms in humans. In addition, we emphasize the value of incorporating diurnal rodent species as more appropriate animal models to study the effects of seasonal changes in light on symptoms of depression and mania that are characteristic of BD in humans.

Genetic Basis of Dual Diagnosis: A Review of Genome-Wide Association Studies (GWAS) Focusing on Patients with Mood or Anxiety Disorders and Co-Occurring Alcohol-Use Disorders

(1) Background: Comorbidity between Alcohol Use Disorders (AUD), mood, and anxiety disorders represents a significant health burden, yet its neurobiological underpinnings are elusive. The current paper reviews all genome-wide association studies conducted in the past ten years, sampling patients with AUD and co-occurring mood or anxiety disorder(s). (2) Methods: In keeping with PRISMA guidelines, we searched EMBASE, Medline/PUBMED, and PsycINFO databases (January 2010 to December 2020), including references of enrolled studies. Study selection was based on predefined criteria and data underwent a multistep revision process. (3) Results: 15 studies were included. Some of them explored dual diagnoses phenotypes directly while others employed correlational analysis based on polygenic risk score approach. Their results support the significant overlap of genetic factors involved in AUDs and mood and anxiety disorders. Comorbidity risk seems to be conveyed by genes engaged in neuronal development, connectivity, and signaling although the precise neuronal pathways and mechanisms remain unclear. (4) Conclusion: given that genes associated with complex traits including comorbid clinical presentations are of small effect, and individually responsible for a very low proportion of the total variance, larger samples consisting of multiple refined comorbid combinations and confirmed by re-sequencing approaches will be necessary to disentangle the genetic architecture of dual diagnosis.

Blockade of alcohol excessive and "relapse" drinking in male mice by pharmacological cryptochrome (CRY) activation

RATIONALE

Metabolic dysfunction, mood disorders, anxiety disorders, and substance abuse disorders are associated with disruptions in circadian rhythm and circadian clock gene machinery. While the effects of alcohol on several core components of the clock genes have been described in rodent models, pharmacological activation or inhibition of clock gene functions has not been studied on alcohol drinking behaviors.

OBJECTIVES

We investigated whether cryptochrome (CRY1/2) activator KL001 altered alcohol intake in mice in excessive and relapse-like alcohol drinking models.

METHODS

Mice, subjected to 3 weeks of chronic intermittent alcohol drinking (IAD) (two-bottle choice, 24-h access every other day) developed excessive alcohol intake and high preference. We evaluated the pharmacological effects of KL001 after either 1-day acute withdrawal from IAD or 1-week chronic withdrawal using the alcohol deprivation effect (ADE) model.

RESULTS

Single pretreatment with KL001 at 1-4 mg kg-1 reduced alcohol intake and preference after acute withdrawal in a dose-related manner. The effect of KL001 on reducing excessive alcohol consumption seems alcohol specific, as the compound does not alter sucrose (caloric reinforcer) or saccharin (noncaloric reinforcer) consumption in mice. Both single- and multiple-dosing regimens with an effective dose of KL001 (4 mg kg-1) prevented the ADE after chronic withdrawal, with no tolerance development after the multi-dosing regimen.

CONCLUSIONS

Pretreatment with KL001 (a CRY1/2 activator) reduces excessive and "relapse" alcohol drinking in mice. Our in vivo results with a CRY activator suggest a possible novel target for alcohol treatment intervention.

Precision medicine for mood disorders: objective assessment, risk prediction, pharmacogenomics, and repurposed drugs

Mood disorders (depression, bipolar disorders) are prevalent and disabling. They are also highly co-morbid with other psychiatric disorders. Currently there are no objective measures, such as blood tests, used in clinical practice, and available treatments do not work in everybody. The development of blood tests, as well as matching of patients with existing and new treatments, in a precise, personalized and preventive fashion, would make a significant difference at an individual and societal level. Early pilot studies by us to discover blood biomarkers for mood state were promising [1], and validated by others [2]. Recent work by us has identified blood gene expression biomarkers that track suicidality, a tragic behavioral outcome of mood disorders, using powerful longitudinal within-subject designs, validated them in suicide completers, and tested them in independent cohorts for ability to assess state (suicidal ideation), and ability to predict trait (future hospitalizations for suicidality) [3-6]. These studies showed good reproducibility with subsequent independent genetic studies [7]. More recently, we have conducted such studies also for pain [8], for stress disorders [9], and for memory/Alzheimer's Disease [10]. We endeavored to use a similar comprehensive approach to identify more definitive biomarkers for mood disorders, that are transdiagnostic, by studying mood in psychiatric disorders patients. First, we used a longitudinal within-subject design and whole-genome gene expression approach to discover biomarkers which track mood state in subjects who had diametric changes in mood state from low to high, from visit to visit, as measured by a simple visual analog scale that we had previously developed (SMS-7). Second, we prioritized these biomarkers using a convergent functional genomics (CFG) approach encompassing in a comprehensive fashion prior published evidence in the field. Third, we validated the biomarkers in an independent cohort of subjects with clinically severe depression (as measured by Hamilton Depression Scale, (HAMD)) and with clinically severe mania (as measured by the Young Mania Rating Scale (YMRS)). Adding the scores from the first three steps into an overall convergent functional evidence (CFE) score, we ended up with 26 top candidate blood gene expression biomarkers that had a CFE score as good as or better than SLC6A4, an empirical finding which we used as a de facto positive control and cutoff. Notably, there was among them an enrichment in genes involved in circadian mechanisms. We further analyzed the biological pathways and networks for the top candidate biomarkers, showing that circadian, neurotrophic, and cell differentiation functions are involved, along with serotonergic and glutamatergic signaling, supporting a view of mood as reflecting energy, activity and growth. Fourth, we tested in independent cohorts of psychiatric patients the ability of each of these 26 top candidate biomarkers to assess state (mood (SMS-7), depression (HAMD), mania (YMRS)), and to predict clinical course (future hospitalizations for depression, future hospitalizations for mania). We conducted our analyses across all patients, as well as personalized by gender and diagnosis, showing increased accuracy with the personalized approach, particularly in women. Again, using SLC6A4 as the cutoff, twelve top biomarkers had the strongest overall evidence for tracking and predicting depression after all four steps: NRG1, DOCK10, GLS, PRPS1, TMEM161B, GLO1, FANCF, HNRNPDL, CD47, OLFM1, SMAD7, and SLC6A4. Of them, six had the strongest overall evidence for tracking and predicting both depression and mania, hence bipolar mood disorders. There were also two biomarkers (RLP3 and SLC6A4) with the strongest overall evidence for mania. These panels of biomarkers have practical implications for distinguishing between depression and bipolar disorder. Next, we evaluated the evidence for our top biomarkers being targets of existing psychiatric drugs, which permits matching patients to medications in a targeted fashion, and the measuring of response to treatment. We also used the biomarker signatures to bioinformatically identify new/repurposed candidate drugs. Top drugs of interest as potential new antidepressants were pindolol, ciprofibrate, pioglitazone and adiphenine, as well as the natural compounds asiaticoside and chlorogenic acid. The last 3 had also been identified by our previous suicidality studies. Finally, we provide an example of how a report to doctors would look for a patient with depression, based on the panel of top biomarkers (12 for depression and bipolar, one for mania), with an objective depression score, risk for future depression, and risk for bipolar switching, as well as personalized lists of targeted prioritized existing psychiatric medications and new potential medications. Overall, our studies provide objective assessments, targeted therapeutics, and monitoring of response to treatment, that enable precision medicine for mood disorders.

Genomic perspectives on the circadian clock hypothesis of psychiatric disorders

Circadian rhythm disturbances are frequently described in psychiatric disorders such as major depressive disorder, bipolar disorder, and schizophrenia. Growing evidence suggests a biological connection between mental health and circadian rhythmicity, including the circadian influence on brain function and mood and the requirement for circadian entrainment by external factors, which is often impaired in mental illness. Mental (as well as physical) health is also adversely affected by circadian misalignment. The marked interindividual differences in this combined susceptibility, in addition to the phenotypic spectrum in traits related both to circadian rhythms and mental health, suggested the possibility of a shared genetic background and that circadian clock genes may also be candidate genes for psychiatric disorders. This hypothesis was further strengthened by observations in animal models where clock genes had been knocked out or mutated. The introduction of genome-wide association studies (GWAS) enabled hypothesis-free testing. GWAS analysis of chronotype confirmed the prominent role of circadian genes in these phenotypes and their extensive polygenicity. However, in GWAS on psychiatric traits, only one clock gene, ARNTL (BMAL1) was identified as one of the few loci differentiating bipolar disorder from schizophrenia, and macaque monkeys where the ARNTL gene has been knocked out display symptoms similar to schizophrenia. Another lesson from genomic analyses is that chronotype has an important genetic correlation with several psychiatric disorders and that this effect is unidirectional. We conclude that the effect of circadian disturbances on psychiatric disorders probably relates to modulation of rhythm parameters and extend beyond the core clock genes themselves.

Blood biomarkers for memory: toward early detection of risk for Alzheimer disease, pharmacogenomics, and repurposed drugs

Short-term memory dysfunction is a key early feature of Alzheimer's disease (AD). Psychiatric patients may be at higher risk for memory dysfunction and subsequent AD due to the negative effects of stress and depression on the brain. We carried out longitudinal within-subject studies in male and female psychiatric patients to discover blood gene expression biomarkers that track short term memory as measured by the retention measure in the Hopkins Verbal Learning Test. These biomarkers were subsequently prioritized with a convergent functional genomics approach using previous evidence in the field implicating them in AD. The top candidate biomarkers were then tested in an independent cohort for ability to predict state short-term memory, and trait future positive neuropsychological testing for cognitive impairment. The best overall evidence was for a series of new, as well as some previously known genes, which are now newly shown to have functional evidence in humans as blood biomarkers: RAB7A, NPC2, TGFB1, GAP43, ARSB, PER1, GUSB, and MAPT. Additional top blood biomarkers include GSK3B, PTGS2, APOE, BACE1, PSEN1, and TREM2, well known genes implicated in AD by previous brain and genetic studies, in humans and animal models, which serve as reassuring de facto positive controls for our whole-genome gene expression discovery approach. Biological pathway analyses implicate LXR/RXR activation, neuroinflammation, atherosclerosis signaling, and amyloid processing. Co-directionality of expression data provide new mechanistic insights that are consistent with a compensatory/scarring scenario for brain pathological changes. A majority of top biomarkers also have evidence for involvement in other psychiatric disorders, particularly stress, providing a molecular basis for clinical co-morbidity and for stress as an early precipitant/risk factor. Some of them are modulated by existing drugs, such as antidepressants, lithium and omega-3 fatty acids. Other drug and nutraceutical leads were identified through bioinformatic drug repurposing analyses (such as pioglitazone, levonorgestrel, salsolidine, ginkgolide A, and icariin). Our work contributes to the overall pathophysiological understanding of memory disorders and AD. It also opens new avenues for precision medicine- diagnostics (assement of risk) as well as early treatment (pharmacogenomically informed, personalized, and preventive).

Alcohol misuse in bipolar disorder. A systematic review and meta-analysis of comorbidity rates

Aims:

To assess the comorbidity rates of alcohol use disorders (AUDs) in bipolar disorder (BD) and to explore possible sources of heterogeneity.

Methods:

Studies were identified through database searches. Meta-analytic techniques were employed to aggregate data on lifetime comorbidity and to explore possible sources of heterogeneity. Funnel plots were used to detect publication bias.

Results:

In clinical studies, AUDs affected more than one in three subjects with BD. Significant heterogeneity was found, which was largely explained by the geographical location of study populations and gender ratio of participants. AUDs affected more than one in five women and two in five men.

Conclusion:

AUDs are highly prevalent in BD. Our study revealed a substantial heterogeneity across studies. Further research including control groups is needed. Patients with BD should be assessed for current and previous AUDs.

Synaptotagmin-7 is a key factor for bipolar-like behavioral abnormalities in mice

The pathogenesis of bipolar disorder (BD) has remained enigmatic, largely because genetic animal models based on identified susceptible genes have often failed to show core symptoms of spontaneous mood cycling. However, pedigree and induced pluripotent stem cell (iPSC)-based analyses have implicated that dysfunction in some key signaling cascades might be crucial for the disease pathogenesis in a subpopulation of BD patients. We hypothesized that the behavioral abnormalities of patients and the comorbid metabolic abnormalities might share some identical molecular mechanism. Hence, we investigated the expression of insulin/synapse dually functioning genes in neurons derived from the iPSCs of BD patients and the behavioral phenotype of mice with these genes silenced in the hippocampus. By these means, we identified synaptotagmin-7 (Syt7) as a candidate risk factor for behavioral abnormalities. We then investigated Syt7 knockout (KO) mice and observed nocturnal manic-like and diurnal depressive-like behavioral fluctuations in a majority of these animals, analogous to the mood cycling symptoms of BD. We treated the Syt7 KO mice with clinical BD drugs including olanzapine and lithium, and found that the drug treatments could efficiently regulate the behavioral abnormalities of the Syt7 KO mice. To further verify whether Syt7 deficits existed in BD patients, we investigated the plasma samples of 20 BD patients and found that the Syt7 mRNA level was significantly attenuated in the patient plasma compared to the healthy controls. We therefore concluded that Syt7 is likely a key factor for the bipolar-like behavioral abnormalities.

Towards precision medicine for stress disorders: diagnostic biomarkers and targeted drugs

The biological fingerprint of environmental adversity may be key to understanding health and disease, as it encompasses the damage induced as well as the compensatory reactions of the organism. Metabolic and hormonal changes may be an informative but incomplete window into the underlying biology. We endeavored to identify objective blood gene expression biomarkers for psychological stress, a subjective sensation with biological roots. To quantify the stress perception at a particular moment in time, we used a simple visual analog scale for life stress in psychiatric patients, a high-risk group. Then, using a stepwise discovery, prioritization, validation, and testing in independent cohort design, we were successful in identifying gene expression biomarkers that were predictive of high-stress states and of future psychiatric hospitalizations related to stress, more so when personalized by gender and diagnosis. One of the top biomarkers that survived discovery, prioritization, validation, and testing was FKBP5, a well-known gene involved in stress response, which serves as a de facto reassuring positive control. We also compared our biomarker findings with telomere length (TL), another well-established biological marker of psychological stress and show that newly identified predictive biomarkers such as NUB1, APOL3, MAD1L1, or NKTR are comparable or better state or trait predictors of stress than TL or FKBP5. Over half of the top predictive biomarkers for stress also had prior evidence of involvement in suicide, and the majority of them had evidence in other psychiatric disorders, providing a molecular underpinning for the effects of stress in those disorders. Some of the biomarkers are targets of existing drugs, of potential utility in patient stratification, and pharmacogenomics approaches. Based on our studies and analyses, the biomarkers with the best overall convergent functional evidence (CFE) for involvement in stress were FKBP5, DDX6, B2M, LAIR1, RTN4, and NUB1. Moreover, the biomarker gene expression signatures yielded leads for possible new drug candidates and natural compounds upon bioinformatics drug repurposing analyses, such as calcium folinate and betulin. Our work may lead to improved diagnosis and treatment for stress disorders such as PTSD, that result in decreased quality of life and adverse outcomes, including addictions, violence, and suicide.

Behavioral, affective, and cognitive alterations induced by individual and combined environmental stressors in rats

OBJECTIVE

To evaluate whether exposing rats to individual or combined environmental stressors triggers endophenotypes related to mood and anxiety disorders, and whether this effect depends on the nature of the behavior (i.e., innate or learned).

METHODS

We conducted a three-phase experimental protocol. In phase I (baseline), animals subjected to mixed schedule of reinforcement were trained to press a lever with a fixed interval of 1 minute and a limited hold of 3 seconds. On the last day of phase I, an open-field test was performed and the animals were divided into four experimental groups (n=8/group). In phase II (repeated stress), each group was exposed to either hot air blast (HAB), paradoxical sleep deprivation (PSD) or both (HAB+PSD group) on alternate days over a 10-day period. Control group animals were not exposed to stressors. In phase III (post-stress evaluation), behavior was analyzed on the first (short-term effects), third (mid-term effects), and fifth (long-term effects) days after repeated stress.

RESULTS

The PSD group presented operant hyperactivity, the HAB group presented spontaneous hypoactivity and anxiety, and the HAB+PSD group presented spontaneous hyperactivity, operant hypoactivity, impulsivity, loss of interest, and cognitive impairment.

CONCLUSION

A combination of environmental stressors (HAB and PSD) may induce endophenotypes related to bipolar disorder.

Epigenetics of the molecular clock and bacterial diversity in bipolar disorder

Objectives The gut microbiome harbors substantially more genetic material than our body cells and has an impact on a huge variety of physiological mechanisms including the production of neurotransmitters and the interaction with brain functions through the gut-brain-axis. Products of microbiota can affect methylation according to preclinical studies. The current investigation aimed at analyzing the correlation between gut microbiome diversity and the methylation of the clock gene ARNTL in individuals with Bipolar Disorder (BD). Methods Genomic DNA was isolated from fasting blood of study participants with BD (n = 32). The methylation analysis of the ARNTL CG site cg05733463 was performed by bisulfite treatment of genomic DNA with the Epitect kit, PCR and pyrosequencing. Additionally, DNA was extracted from stool samples and subjected to 16S rRNA sequencing. QIIME was used to analyze microbiome data. Results Methylation status of the ARNTL CpG position cg05733463 correlated significantly with bacterial diversity (Simpson index: r= -0.389, p =  0.0238) and evenness (Simpson evenness index: r= -0.358, p =  0.044). Furthermore, bacterial diversity differed significantly between euthymia and depression (F(1,30) = 4.695, p =  0.039). Discussion The results of our pilot study show that bacterial diversity differs between euthymia and depression. Interestingly, gut microbiome diversity and evenness correlate negatively with methylation of ARNTL, which is known to regulate monoamine oxidase A transcription. We propose that alterations in overall diversity of the gut microbiome represent an internal environmental factor that has an epigenetic impact on the clock gene ARNTL which is thought to be involved in BD pathogenesis.

High Exploratory Phenotype Rats Exposed to Environmental Stressors Present Memory Deficits Accompanied by Immune-Inflammatory/Oxidative Alterations: Relevance to the Relationship Between Temperament and Mood Disorders

Low-exploratory (LE) and high-exploratory (HE) rodents mimic human depressive and hyperthymic temperaments, respectively. Mood disorders (MD) may be developed by the exposure of these temperaments to environmental stress (ES). Psychiatric symptoms severity in MD patients is related to the magnitude of memory impairment. Thus, we aimed at studying the consequences of the exposure of LE and HE male Wistar rats, during periadolescence, to a combination of ES, namely, paradoxical sleep deprivation (PSD) and unpredictable stress (US), on anxiety-related behavior in the plus maze test, working (WM) and declarative memory (DM) performance. We also evaluated hippocampal immune-inflammatory/oxidative, as consequences of ES, and prevention of ES-induced alterations by the mood-stabilizing drugs, lithium and valproate. Medium exploratory (ME) control rats were used for comparisons with HE- and LE-control rats. We observed that HE-controls presented increased anxiolytic behavior that was significantly increased by ES exposure, whereas LE-controls presented increased anxiety-like behavior relative to ME-controls. Lithium and valproate prevented anxiolytic alterations in HE+ES rats. HE+ES- and LE+ES-rats presented WM and DM deficits. Valproate and lithium prevented WM deficits in LE-PSD+US rats. Lithium prevented DM impairment in HE+ES-rats. Hippocampal levels of reduced glutathione (GSH) increased four-fold in HE+ES-rats, being prevented by valproate and lithium. All groups of LE+ES-rats presented increased levels of GSH in relation to controls. Increments in lipid peroxidation in LE+ES- and HE+ES-rats were prevented by valproate in HE+ES-rats and by both drugs in LE+ES-rats. Nitrite levels were increased in HE+ES- and LE+ES-rats (five-fold increase), which was prevented by both drugs in LE+ES-rats. HE+ES-rats presented a two-fold increase in the inducible nitric oxide synthase (iNOS) expression that was prevented by lithium. HE+ES-rats showed increased hippocampal and plasma levels of interleukin (IL)-1β and IL-4. Indoleamine 2, 3-dioxygenase 1 (IDO1) was increased in HE+ES- and LE+ES-rats, while tryptophan 2,3-dioxygenase (TDO2) was increased only in HE+ES-rats. Altogether, our results showed that LE- and HE-rats exposed to ES present distinct anxiety-related behavior and similar memory deficits. Furthermore, HE+ES-rats presented more brain and plasma inflammatory alterations that were partially prevented by the mood-stabilizing drugs. These alterations in HE+ES-rats may possibly be related to the development of mood symptoms.

Towards precision medicine for pain: diagnostic biomarkers and repurposed drugs

We endeavored to identify objective blood biomarkers for pain, a subjective sensation with a biological basis, using a stepwise discovery, prioritization, validation, and testing in independent cohorts design. We studied psychiatric patients, a high risk group for co-morbid pain disorders and increased perception of pain. For discovery, we used a powerful within-subject longitudinal design. We were successful in identifying blood gene expression biomarkers that were predictive of pain state, and of future emergency department (ED) visits for pain, more so when personalized by gender and diagnosis. MFAP3, which had no prior evidence in the literature for involvement in pain, had the most robust empirical evidence from our discovery and validation steps, and was a strong predictor for pain in the independent cohorts, particularly in females and males with PTSD. Other biomarkers with best overall convergent functional evidence for involvement in pain were GNG7, CNTN1, LY9, CCDC144B, and GBP1. Some of the individual biomarkers identified are targets of existing drugs. Moreover, the biomarker gene expression signatures were used for bioinformatic drug repurposing analyses, yielding leads for possible new drug candidates such as SC-560 (an NSAID), and amoxapine (an antidepressant), as well as natural compounds such as pyridoxine (vitamin B6), cyanocobalamin (vitamin B12), and apigenin (a plant flavonoid). Our work may help mitigate the diagnostic and treatment dilemmas that have contributed to the current opioid epidemic.

Prospects for circadian treatment of mood disorders

Disruption of circadian clocks is strongly associated with mood disorders. Chronotherapies targeting circadian rhythms have been shown to be very effective treatments of mood disorders, but still are not widely used in clinical practice. The mechanisms by which circadian disruption leads to mood disorders are poorly characterized and, therefore, may not convince clinicians to apply chronotherapies. Hence, in this review, we describe specific potential mechanisms, in order to make this connection more credible to clinicians. We believe that four major features of disrupted clocks may contribute to the development of mood disorders: (1) loss of synchronization to environmental 24-h rhythms, (2) internal desynchronization among body clocks, (3) low rhythm amplitude, and (4) changes in sleep architecture. Discussing these attributes and giving plausible examples, we will discuss prospects for relatively simple chronotherapies addressing these features that are easy to implement in clinical practice. Key messages In this review, we describe specific potential mechanisms by which disrupted clocks may contribute to the development of mood disorders: (1) loss of synchronization to environmental 24-h rhythms, (2) internal desynchronization among body clocks, (3) low rhythm amplitude, and (4) changes in sleep architecture. We provide prospects for relatively simple chronotherapies addressing these features that are easy to implement in clinical practice.

Protein Kinase C Activity and Delayed Recovery of Sleep-Wake Cycle in Mouse Model of Bipolar Disorder

OBJECTIVE

Previous studies reported the delayed recovery group after circadian rhythm disruption in mice showed higher quinpiroleinduced locomotor activity. This study aimed to compare not only Protein Kinase C (PKC) activities in frontal, striatal, hippocampus and cerebellum, but also relative PKC activity ratios among brain regions according to recovery of circadian rhythm.

METHODS

The circadian rhythm disruption protocol was applied to eight-week-old twenty male Institute Cancer Research mice. The circadian rhythm recovery patterns were collected through motor activities measured by Mlog system. Depressive and manic proneness were examined by forced swim test and quinpirole-induced open field test respectively. Enzyme-linked immunosorbent assay was employed to measure PKC activities.

RESULTS

The delayed recovery group presented greater locomotor activities than the early recovery group (p=0.033). The delayed recovery group had significantly lower frontal PKC activity than the other (p=0.041). The former showed lower frontal/cerebellar PKC activity ratio (p=0.047) but higher striatal/frontal (p=0.038) and hippocampal/frontal (p=0.007) PKC activities ratios than the latter.

CONCLUSION

These findings support potential mechanism of delayed recovery after circadian disruption in bipolar animal model could be an alteration of relative PKC activities among mood regulation related brain regions. It is required to investigate the PKC downstream signaling related to the delayed recovery pattern.

CNS Drug Development, Lessons Learned, Part 4: The Role of Brain Circuitry and Genes-Tasimelteon as an Example

This is the fourth in a series of columns discussing the rational and targeted development of drugs to affect specific central nervous system (CNS) circuits in specific ways based on knowledge gained by molecular biology and the human genome project. The first column in this series described 6 CNS drugs with novel mechanisms of action developed over the last 25 years. The second column discussed differences between syndromic diagnoses as exemplified by the third through the fifth editions of the Diagnostic and Statistical Manual of Mental Disorders (DSM III through DSM-5) and the new approach to psychiatric diagnoses championed by the National Institute of Mental Health in their Research Domain Criteria Initiative. The third column reviewed the last 9 years of drug development contrasting the development of drugs in other therapeutic areas (eg, cancer) with psychiatric and related CNS-active drugs. This column extends the discussion of modern drug development for psychiatric and other CNS-related indications, using the development of tasimelteon as an example of how modern drug development focuses rationally on novel targets of interest while simultaneously achieving "specificity." Tasimelteon, which is indicated for the treatment of non-24-hour sleep-wake disorder, was developed to be a selective agonist at the melatonin MT1 and MT2 receptors, with limited or no effects at other pharmacologically relevant receptors and enzymes to minimize the potential for off-target effects (eg, nuisance side effects), toxicity, drug-drug interactions, and effects on oxidative drug metabolizing enzymes. The next column in this series will continue the discussion of the development of CNS drugs with novel mechanisms of action, using suvorexant, which targets orexin-1 and orexin-2 receptors, to illustrate the preclinical and human studies that were carried out to assess its safety as part of a successful new drug application.

Animal models for bipolar disorder: from bedside to the cage

Bipolar disorder is characterized by recurrent manic and depressive episodes. Patients suffering from this disorder experience dramatic mood swings with a wide variety of typical behavioral facets, affecting overall activity, energy, sexual behavior, sense of self, self-esteem, circadian rhythm, cognition, and increased risk for suicide. Effective treatment options are limited and diagnosis can be complicated. To overcome these obstacles, a better understanding of the neurobiology underlying bipolar disorder is needed. Animal models can be useful tools in understanding brain mechanisms associated with certain behavior. The following review discusses several pathological aspects of humans suffering from bipolar disorder and compares these findings with insights obtained from several animal models mimicking diverse facets of its symptomatology. Various sections of the review concentrate on specific topics that are relevant in human patients, namely circadian rhythms, neurotransmitters, focusing on the dopaminergic system, stressful environment, and the immune system. We then explain how these areas have been manipulated to create animal models for the disorder. Even though several approaches have been conducted, there is still a lack of adequate animal models for bipolar disorder. Specifically, most animal models mimic only mania or depression and only a few include the cyclical nature of the human condition. Future studies could therefore focus on modeling both episodes in the same animal model to also have the possibility to investigate the switch from mania-like behavior to depressive-like behavior and vice versa. The use of viral tools and a focus on circadian rhythms and the immune system might make the creation of such animal models possible.

Forebrain-specific ablation of phospholipase Cγ1 causes manic-like behavior

Manic episodes are one of the major diagnostic symptoms in a spectrum of neuropsychiatric disorders that include schizophrenia, obsessive-compulsive disorder and bipolar disorder (BD). Despite a possible association between BD and the gene encoding phospholipase Cγ1 (PLCG1), its etiological basis remains unclear. Here, we report that mice lacking phospholipase Cγ1 (PLCγ1) in the forebrain (Plcg1^f/f; CaMKII) exhibit hyperactivity, decreased anxiety-like behavior, reduced depressive-related behavior, hyperhedonia, hyperphagia, impaired learning and memory and exaggerated startle responses. Inhibitory transmission in hippocampal pyramidal neurons and striatal dopamine receptor D1-expressing neurons of Plcg1-deficient mice was significantly reduced. The decrease in inhibitory transmission is likely due to a reduced number of γ-aminobutyric acid (GABA)-ergic boutons, which may result from impaired localization and/or stabilization of postsynaptic CaMKII (Ca²⁺/calmodulin-dependent protein kinase II) at inhibitory synapses. Moreover, mutant mice display impaired brain-derived neurotrophic factor-tropomyosin receptor kinase B-dependent synaptic plasticity in the hippocampus, which could account for deficits of spatial memory. Lithium and valproate, the drugs presently used to treat mania associated with BD, rescued the hyperactive phenotypes of Plcg1^f/f; CaMKII mice. These findings provide evidence that PLCγ1 is critical for synaptic function and plasticity and that the loss of PLCγ1 from the forebrain results in manic-like behavior.

Precision medicine for suicidality: from universality to subtypes and personalization

Suicide remains a clear, present and increasing public health problem, despite being a potentially preventable tragedy. Its incidence is particularly high in people with overt or un(der)diagnosed psychiatric disorders. Objective and precise identification of individuals at risk, ways of monitoring response to treatments and novel preventive therapeutics need to be discovered, employed and widely deployed. We sought to investigate whether blood gene expression biomarkers for suicide (that is, a 'liquid biopsy' approach) can be identified that are more universal in nature, working across psychiatric diagnoses and genders, using larger cohorts than in previous studies. Such markers may reflect and/or be a proxy for the core biology of suicide. We were successful in this endeavor, using a comprehensive stepwise approach, leading to a wealth of findings. Steps 1, 2 and 3 were discovery, prioritization and validation for tracking suicidality, resulting in a Top Dozen list of candidate biomarkers comprising the top biomarkers from each step, as well as a larger list of 148 candidate biomarkers that survived Bonferroni correction in the validation step. Step 4 was testing the Top Dozen list and Bonferroni biomarker list for predictive ability for suicidal ideation (SI) and for future hospitalizations for suicidality in independent cohorts, leading to the identification of completely novel predictive biomarkers (such as CLN5 and AK2), as well as reinforcement of ours and others previous findings in the field (such as SLC4A4 and SKA2). Additionally, we examined whether subtypes of suicidality can be identified based on mental state at the time of high SI and identified four potential subtypes: high anxiety, low mood, combined and non-affective (psychotic). Such subtypes may delineate groups of individuals that are more homogenous in terms of suicidality biology and behavior. We also studied a more personalized approach, by psychiatric diagnosis and gender, with a focus on bipolar males, the highest risk group. Such a personalized approach may be more sensitive to gender differences and to the impact of psychiatric co-morbidities and medications. We compared testing the universal biomarkers in everybody versus testing by subtypes versus personalized by gender and diagnosis, and show that the subtype and personalized approaches permit enhanced precision of predictions for different universal biomarkers. In particular, LHFP appears to be a strong predictor for suicidality in males with depression. We also directly examined whether biomarkers discovered using male bipolars only are better predictors in a male bipolar independent cohort than universal biomarkers and show evidence for a possible advantage of personalization. We identified completely novel biomarkers (such as SPTBN1 and C7orf73), and reinforced previously known biomarkers (such as PTEN and SAT1). For diagnostic ability testing purposes, we also examined as predictors phenotypic measures as apps (for suicide risk (CFI-S, Convergent Functional Information for Suicidality) and for anxiety and mood (SASS, Simplified Affective State Scale)) by themselves, as well as in combination with the top biomarkers (the combination being our a priori primary endpoint), to provide context and enhance precision of predictions. We obtained area under the curves of 90% for SI and 77% for future hospitalizations in independent cohorts. Step 5 was to look for mechanistic understanding, starting with examining evidence for the Top Dozen and Bonferroni biomarkers for involvement in other psychiatric and non-psychiatric disorders, as a mechanism for biological predisposition and vulnerability. The biomarkers we identified also provide a window towards understanding the biology of suicide, implicating biological pathways related to neurogenesis, programmed cell death and insulin signaling from the universal biomarkers, as well as mTOR signaling from the male bipolar biomarkers. In particular, HTR2A increase coupled with ARRB1 and GSK3B decreases in expression in suicidality may provide a synergistic mechanistical corrective target, as do SLC4A4 increase coupled with AHCYL1 and AHCYL2 decrease. Step 6 was to move beyond diagnostics and mechanistical risk assessment, towards providing a foundation for personalized therapeutics. Items scored positive in the CFI-S and subtypes identified by SASS in different individuals provide targets for personalized (psycho)therapy. Some individual biomarkers are targets of existing drugs used to treat mood disorders and suicidality (lithium, clozapine and omega-3 fatty acids), providing a means toward pharmacogenomics stratification of patients and monitoring of response to treatment. Such biomarkers merit evaluation in clinical trials. Bioinformatics drug repurposing analyses with the gene expression biosignatures of the Top Dozen and Bonferroni-validated universal biomarkers identified novel potential therapeutics for suicidality, such as ebselen (a lithium mimetic), piracetam (a nootropic), chlorogenic acid (a polyphenol) and metformin (an antidiabetic and possible longevity promoting drug). Finally, based on the totality of our data and of the evidence in the field to date, a convergent functional evidence score prioritizing biomarkers that have all around evidence (track suicidality, predict it, are reflective of biological predisposition and are potential drug targets) brought to the fore APOE and IL6 from among the universal biomarkers, suggesting an inflammatory/accelerated aging component that may be a targetable common denominator.

Non-nuclear Pool of Splicing Factor SFPQ Regulates Axonal Transcripts Required for Normal Motor Development

Recent progress revealed the complexity of RNA processing and its association to human disorders. Here, we unveil a new facet of this complexity. Complete loss of function of the ubiquitous splicing factor SFPQ affects zebrafish motoneuron differentiation cell autonomously. In addition to its nuclear localization, the protein unexpectedly localizes to motor axons. The cytosolic version of SFPQ abolishes motor axonal defects, rescuing key transcripts, and restores motility in the paralyzed sfpq null mutants, indicating a non-nuclear processing role in motor axons. Novel variants affecting the conserved coiled-coil domain, so far exclusively found in fALS exomes, specifically affect the ability of SFPQ to localize in axons. They broadly rescue morphology and motility in the zebrafish mutant, but alter motor axon morphology, demonstrating functional requirement for axonal SFPQ. Altogether, we uncover the axonal function of the splicing factor SFPQ in motor development and highlight the importance of the coiled-coil domain in this process.

Video Abstract

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SFPQ splicing factor is present in motor axons

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Non-nuclear SFPQ is able to drive axon maturation and connectivity

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Loss of axonal SFPQ affects axonal morphology

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Coiled-coil domain of the protein is important for non-nuclear localization

Alterations in splenic function and gene expression in mice with depressive-like behavior induced by exposure to corticosterone

Depressed patients present with increased cortisol levels and attenuated immune responses. However, little is known about the association between depression and the spleen, as this is the largest peripheral immune organ. In this study, we examined alterations in splenic function and gene expression in mice with depressive-like behavior, well as the expression of certain proteins in related pathways. A mouse model of depression was established with the use of corticosterone. Splenic function and histopathology were assessed using Wright and H&E staining. The Agilent Whole Mouse Genome Oligo Microarray containing >41,174 transcript probes was used to measure the levels of gene-expression in the spleens from control and model mice, and the levels of certain proteins associated with depression were measured by western blot analysis in the brain and spleen separately. We found that splenic function and immunity in the mice with depressive-like behavior were markedly impaired. A total of 53 genes exhibited a differential response in the mice with depressive-like behavior, 11 of which were more notable, including collagen, type VI, α5 (Col6a5), immunoglobulin superfamily, member 11 (Igsf11), D site albumin promoter binding protein (Dbp), tachykinin 2 (Tac2) and γ-aminobutyric acid B receptor 2 (Gabbr2). Pathway analysis revealed that the amino acid biosynthesis and the clock gene pathways were more meaningful among these genes. The levels of GABBR2, DBP and substance P (SP; encoded by the Tac2 gene) related proteins in the brain were markedly downregulated, and similar results were observed in the spleen. The anti-depressant, fluoxetine, reversed the changes in the levels of these proteins. The findings of our study regarding changes occurring in the spleen during depression may indirectly elucidate and shed light into the pathogenesis of depression and depressive-like behavior.

Utilization of Diurnal Rodents in the Research of Depression

Preclinical Research Most neuropsychiatric research, including that related to the circadian system, is performed using nocturnal animals, mainly laboratory mice and rats. Mood disorders are known to be associated with circadian rhythm abnormalities, but the mechanisms by which circadian rhythm disruptions interact with depression remain unclear. As the circadian system of diurnal and nocturnal mammals differs, we previously suggested that the utilization of diurnal animal models may be advantageous for understanding these relations. During the last 10 years, we and others established the validity of several diurnal rodent species as a model for the interactions between circadian rhythms and depression. Diurnal rodents respond to photoperiod manipulation in a similar way to humans, the behavioral outcome is directly related to the circadian system, and treatment that is effective in patients is also effective in the model. Moreover, less effective treatments in patients are also less effective in the model. We, therefore, suggest that using diurnal animal models to study circadian rhythms-related affective disorders, such as depression, will provide new insights that will hopefully lead to the development of more effective treatments. Drug Dev Res 77 : 347-356, 2016. © 2016 Wiley Periodicals, Inc.

Mood, stress and longevity: convergence on ANK3

Antidepressants have been shown to improve longevity in C. elegans. It is plausible that orthologs of genes involved in mood regulation and stress response are involved in such an effect. We sought to understand the underlying biology. First, we analyzed the transcriptome from worms treated with the antidepressant mianserin, previously identified in a large-scale unbiased drug screen as promoting increased lifespan in worms. We identified the most robust treatment-related changes in gene expression, and identified the corresponding human orthologs. Our analysis uncovered a series of genes and biological pathways that may be at the interface between antidepressant effects and longevity, notably pathways involved in drug metabolism/degradation (nicotine and melatonin). Second, we examined which of these genes overlap with genes which may be involved in depressive symptoms in an aging non-psychiatric human population (n=3577), discovered using a genome-wide association study (GWAS) approach in a design with extremes of distribution of phenotype. Third, we used a convergent functional genomics (CFG) approach to prioritize these genes for relevance to mood disorders and stress. The top gene identified was ANK3. To validate our findings, we conducted genetic and gene-expression studies, in C. elegans and in humans. We studied C. elegans inactivating mutants for ANK3/unc-44, and show that they survive longer than wild-type, particularly in older worms, independently of mianserin treatment. We also show that some ANK3/unc-44 expression is necessary for the effects of mianserin on prolonging lifespan and survival in the face of oxidative stress, particularly in younger worms. Wild-type ANK3/unc-44 increases in expression with age in C. elegans, and is maintained at lower youthful levels by mianserin treatment. These lower levels may be optimal in terms of longevity, offering a favorable balance between sufficient oxidative stress resistance in younger worms and survival effects in older worms. Thus, ANK3/unc-44 may represent an example of antagonistic pleiotropy, in which low-expression level in young animals are beneficial, but the age-associated increase becomes detrimental. Inactivating mutations in ANK3/unc-44 reverse this effect and cause detrimental effects in young animals (sensitivity to oxidative stress) and beneficial effect in old animals (increased survival). In humans, we studied if the most significant single nucleotide polymorphism (SNP) for depressive symptoms in ANK3 from our GWAS has a relationship to lifespan, and show a trend towards longer lifespan in individuals with the risk allele for depressive symptoms in men (odds ratio (OR) 1.41, P=0.031) but not in women (OR 1.08, P=0.33). We also examined whether ANK3, by itself or in a panel with other top CFG-prioritized genes, acts as a blood gene-expression biomarker for biological age, in two independent cohorts, one of live psychiatric patients (n=737), and one of suicide completers from the coroner's office (n=45). We show significantly lower levels of ANK3 expression in chronologically younger individuals than in middle age individuals, with a diminution of that effect in suicide completers, who presumably have been exposed to more severe and acute negative mood and stress. Of note, ANK3 was previously reported to be overexpressed in fibroblasts from patients with Hutchinson-Gilford progeria syndrome, a form of accelerated aging. Taken together, these studies uncover ANK3 and other genes in our dataset as biological links between mood, stress and longevity/aging, that may be biomarkers as well as targets for preventive or therapeutic interventions. Drug repurposing bioinformatics analyses identified the relatively innocuous omega-3 fatty acid DHA (docosahexaenoic acid), piracetam, quercetin, vitamin D and resveratrol as potential longevity promoting compounds, along with a series of existing drugs, such as estrogen-like compounds, antidiabetics and sirolimus/rapamycin. Intriguingly, some of our top candidate genes for mood and stress-modulated longevity were changed in expression in opposite direction in previous studies in the Alzheimer disease. Additionally, a whole series of others were changed in expression in opposite direction in our previous studies on suicide, suggesting the possibility of a "life switch" actively controlled by mood and stress.

Towards understanding and predicting suicidality in women: biomarkers and clinical risk assessment

Women are under-represented in research on suicidality to date. Although women have a lower rate of suicide completion than men, due in part to the less-violent methods used, they have a higher rate of suicide attempts. Our group has previously identified genomic (blood gene expression biomarkers) and clinical information (apps) predictors for suicidality in men. We now describe pilot studies in women. We used a powerful within-participant discovery approach to identify genes that change in expression between no suicidal ideation (no SI) and high suicidal ideation (high SI) states (n=12 participants out of a cohort of 51 women psychiatric participants followed longitudinally, with diagnoses of bipolar disorder, depression, schizoaffective disorder and schizophrenia). We then used a Convergent Functional Genomics (CFG) approach to prioritize the candidate biomarkers identified in the discovery step by using all the prior evidence in the field. Next, we validated for suicidal behavior the top-ranked biomarkers for SI, in a demographically matched cohort of women suicide completers from the coroner's office (n=6), by assessing which markers were stepwise changed from no SI to high SI to suicide completers. We then tested the 50 biomarkers that survived Bonferroni correction in the validation step, as well as top increased and decreased biomarkers from the discovery and prioritization steps, in a completely independent test cohort of women psychiatric disorder participants for prediction of SI (n=33) and in a future follow-up cohort of psychiatric disorder participants for prediction of psychiatric hospitalizations due to suicidality (n=24). Additionally, we examined how two clinical instruments in the form of apps, Convergent Functional Information for Suicidality (CFI-S) and Simplified Affective State Scale (SASS), previously tested in men, perform in women. The top CFI-S item distinguishing high SI from no SI states was the chronic stress of social isolation. We then showed how the clinical information apps combined with the 50 validated biomarkers into a broad predictor (UP-Suicide), our apriori primary end point, predicts suicidality in women. UP-Suicide had a receiver-operating characteristic (ROC) area under the curve (AUC) of 82% for predicting SI and an AUC of 78% for predicting future hospitalizations for suicidality. Some of the individual components of the UP-Suicide showed even better results. SASS had an AUC of 81% for predicting SI, CFI-S had an AUC of 84% and the combination of the two apps had an AUC of 87%. The top biomarker from our sequential discovery, prioritization and validation steps, BCL2, predicted future hospitalizations due to suicidality with an AUC of 89%, and the panel of 50 validated biomarkers (BioM-50) predicted future hospitalizations due to suicidality with an AUC of 94%. The best overall single blood biomarker for predictions was PIK3C3 with an AUC of 65% for SI and an AUC of 90% for future hospitalizations. Finally, we sought to understand the biology of the biomarkers. BCL2 and GSK3B, the top CFG scoring validated biomarkers, as well as PIK3C3, have anti-apoptotic and neurotrophic effects, are decreased in expression in suicidality and are known targets of the anti-suicidal mood stabilizer drug lithium, which increases their expression and/or activity. Circadian clock genes were overrepresented among the top markers. Notably, PER1, increased in expression in suicidality, had an AUC of 84% for predicting future hospitalizations, and CSNK1A1, decreased in expression, had an AUC of 96% for predicting future hospitalizations. Circadian clock abnormalities are related to mood disorder, and sleep abnormalities have been implicated in suicide. Docosahexaenoic acid signaling was one of the top biological pathways overrepresented in validated biomarkers, which is of interest given the potential therapeutic and prophylactic benefits of omega-3 fatty acids. Some of the top biomarkers from the current work in women showed co-directionality of change in expression with our previous work in men, whereas others had changes in opposite directions, underlying the issue of biological context and differences in suicidality between the two genders. With this study, we begin to shed much needed light in the area of female suicidality, identify useful objective predictors and help understand gender commonalities and differences. During the conduct of the study, one participant committed suicide. In retrospect, when the analyses were completed, her UP-Suicide risk prediction score was at the 100 percentile of all participants tested.

Modeling mania in preclinical settings: A comprehensive review

The current pathophysiological understanding of mechanisms leading to onset and progression of bipolar manic episodes remains limited. At the same time, available animal models for mania have limited face, construct, and predictive validities. Additionally, these models fail to encompass recent pathophysiological frameworks of bipolar disorder (BD), e.g. neuroprogression. Therefore, there is a need to search for novel preclinical models for mania that could comprehensively address these limitations. Herein we review the history, validity, and caveats of currently available animal models for mania. We also review new genetic models for mania, namely knockout mice for genes involved in neurotransmission, synapse formation, and intracellular signaling pathways. Furthermore, we review recent trends in preclinical models for mania that may aid in the comprehension of mechanisms underlying the neuroprogressive and recurring nature of BD. In conclusion, the validity of animal models for mania remains limited. Nevertheless, novel (e.g. genetic) animal models as well as adaptation of existing paradigms hold promise.

Animal models of bipolar mania: The past, present and future

Bipolar disorder (BD) is the sixth leading cause of disability in the world according to the World Health Organization and affects nearly six million (∼2.5% of the population) adults in the United State alone each year. BD is primarily characterized by mood cycling of depressive (e.g., helplessness, reduced energy and activity, and anhedonia) and manic (e.g., increased energy and hyperactivity, reduced need for sleep, impulsivity, reduced anxiety and depression), episodes. The following review describes several animal models of bipolar mania with a focus on more recent findings using genetically modified mice, including several with the potential of investigating the mechanisms underlying 'mood' cycling (or behavioral switching in rodents). We discuss whether each of these models satisfy criteria of validity (i.e., face, predictive, and construct), while highlighting their strengths and limitations. Animal models are helping to address critical questions related to pathophysiology of bipolar mania, in an effort to more clearly define necessary targets of first-line medications, lithium and valproic acid, and to discover novel mechanisms with the hope of developing more effective therapeutics. Future studies will leverage new technologies and strategies for integrating animal and human data to reveal important insights into the etiology, pathophysiology, and treatment of BD.

Chronic treatment with mood stabilizer lithium inhibits amphetamine-induced risk-taking manic-like behaviors

A lack of behavioral tests and animal models for manic-depressive bipolar disorder is recognized as an important factor limiting development of novel pharmaceutical treatments for the disorder. Repeated amphetamine-induced hyperactivity is a commonly used animal model for mania. However, hyperactivity represents only one facet of mania and is also seen in other disorders. Increased engagement in risk taking behavior is frequently observed in the manic phase of bipolar disorder. In the present study, we analyzed the effect of the most commonly used mood stabilizer lithium on repeated amphetamine treatment-induced risk-taking behaviors in rats using elevated plus maze and wire-beam bridge tests. We found that repeated amphetamine treatment not only increased locomotor activity, but also increased risk taking behaviors in rats, and further that chronic lithium treatment inhibited the amphetamine-increased risk taking behavior. Our studies suggest that these tests may be useful tools to analyze the pharmacological validity of new and improved anti-manic drugs in animals.

A cross-species genetic analysis identifies candidate genes for mouse anxiety and human bipolar disorder

Bipolar disorder (BD) is a significant neuropsychiatric disorder with a lifetime prevalence of ~1%. To identify genetic variants underlying BD genome-wide association studies (GWAS) have been carried out. While many variants of small effect associated with BD have been identified few have yet been confirmed, partly because of the low power of GWAS due to multiple comparisons being made. Complementary mapping studies using murine models have identified genetic variants for behavioral traits linked to BD, often with high power, but these identified regions often contain too many genes for clear identification of candidate genes. In the current study we have aligned human BD GWAS results and mouse linkage studies to help define and evaluate candidate genes linked to BD, seeking to use the power of the mouse mapping with the precision of GWAS. We use quantitative trait mapping for open field test and elevated zero maze data in the largest mammalian model system, the BXD recombinant inbred mouse population, to identify genomic regions associated with these BD-like phenotypes. We then investigate these regions in whole genome data from the Psychiatric Genomics Consortium's bipolar disorder GWAS to identify candidate genes associated with BD. Finally we establish the biological relevance and pathways of these genes in a comprehensive systems genetics analysis. We identify four genes associated with both mouse anxiety and human BD. While TNR is a novel candidate for BD, we can confirm previously suggested associations with CMYA5, MCTP1, and RXRG. A cross-species, systems genetics analysis shows that MCTP1, RXRG, and TNR coexpress with genes linked to psychiatric disorders and identify the striatum as a potential site of action. CMYA5, MCTP1, RXRG, and TNR are associated with mouse anxiety and human BD. We hypothesize that MCTP1, RXRG, and TNR influence intercellular signaling in the striatum.

Investigation of associations between NR1D1, RORA and RORB genes and bipolar disorder

Several genes that are involved in the regulation of circadian rhythms are implicated in the susceptibility to bipolar disorder (BD). The current study aimed to investigate the relationships between genetic variants in NR1D1 RORA, and RORB genes and BD in the Han Chinese population. We conducted a case-control genetic association study with two samples of BD patients and healthy controls. Sample I consisted of 280 BD patients and 200 controls. Sample II consisted of 448 BD patients and 1770 healthy controls. 27 single nucleotide polymorphisms in the NR1D1, RORA, and RORB genes were genotyped using GoldenGate VeraCode assays in sample I, and 492 markers in the three genes were genotyped using Affymetrix Genome-Wide CHB Array in sample II. Single marker and gene-based association analyses were performed using PLINK. A combined p-value for the joining effects of all markers within a gene was calculated using the rank truncated product method. Multifactor dimensionality reduction (MDR) method was also applied to test gene-gene interactions in sample I. All markers were in Hardy-Weinberg equilibrium (P>0.001). In sample I, the associations with BD were observed for rs4774388 in RORA (OR = 1.53, empirical p-value, P = 0.024), and rs1327836 in RORB (OR = 1.75, P = 0.003). In Sample II, there were 45 SNPs showed associations with BD, and the most significant marker in RORA was rs11639084 (OR = 0.69, P = 0.002), and in RORB was rs17611535 (OR = 3.15, P = 0.027). A combined p-value of 1.6×10−6, 0.7, and 1.0 was obtained for RORA, RORB and NR1D1, respectively, indicting a strong association for RORA with the risk of developing BD. A four way interaction was found among markers in NR1D1, RORA, and RORB with the testing accuracy 53.25% and a cross-validation consistency of 8 out of 10. In sample II, 45 markers had empirical p-values less than 0.05. The most significant markers in RORA and RORB genes were rs11639084 (OR = 0.69, P = 0.002), and rs17611535 (OR = 3.15, P = 0.027), respectively. Gene-based association was significant for RORA gene (P = 0.0007). Our results support for the involvement of RORs genes in the risk of developing BD. Investigation of the functional properties of genes in the circadian pathway may further enhance our understanding about the pathogenesis of bipolar illness.

New ways of modeling bipolar disorder

There is a well-known deficiency in valid animal models for bipolar disorder. Developing the single ideal model for the disorder-one that will represent its full scope-will probably not be possible until we have a much better understanding of the underlying pathology. Yet, intermediate models, even with partial validity, are critical in order to advance our knowledge and put us into position to develop even better models. The present article discusses the various efforts under way to develop the best models based on our current level of understanding. These efforts include (1) identifying new tests, (2) developing models based on the endophenotypes approach, (3) identifying the best rodent strains, (4) identifying the most appropriate species, (5) segregating susceptible versus resilient animals, and (6) segregating animals that respond or do not respond to treatment. It is suggested that a combined approach that includes these directions and others can result in better models with higher validity that will offer significant help in advancing research on bipolar disorder and developing new and better treatments.

Circadian clock and stress interactions in the molecular biology of psychiatric disorders

Many psychiatric disorders are characterized by circadian rhythm abnormalities, including disturbed sleep/wake cycles, changes in locomotor activity, and abnormal endocrine function. Animal models with mutations in circadian "clock genes" commonly show disturbances in reward processing, locomotor activity and novelty seeking behaviors, further supporting the idea of a connection between the circadian clock and psychiatric disorders. However, if circadian clock dysfunction is a common risk factor for multiple psychiatric disorders, it is unknown if and how these putative clock abnormalities could be expressed differently, and contribute to multiple, distinct phenotypes. One possible explanation is that the circadian clock modulates the biological responses to stressful environmental factors that vary with an individual's experience. It is known that the circadian clock and the stress response systems are closely related: Circadian clock genes regulate the physiological sensitivity to and rhythmic release of glucocorticoids (GC). In turn, GCs have reciprocal effects on the clock. Since stressful life events or increased vulnerability to stress are risk factors for multiple psychiatric disorders, including post-traumatic stress disorder (PTSD), attention deficit hyperactivity disorder (ADHD), bipolar disorder (BD), major depressive disorder (MDD), alcohol use disorder (AUD) and schizophrenia (SCZ), we propose that modulation of the stress response is a common mechanism by which circadian clock genes affect these illnesses. Presently, we review how molecular components of the circadian clock may contribute to these six psychiatric disorders, and present the hypothesis that modulation of the stress response may constitute a common mechanism by which the circadian clock affects multiple psychiatric disorders.

Adenosinergic regulation of striatal clock gene expression and ethanol intake during constant light

Circadian rhythm and sleep disruptions occur frequently in individuals with alcohol use disorders (AUD) and present significant barriers to treatment. Recently, a variant of adenosine transporter, equilibrative nucleoside transporter 1 (ENT1), was associated with the co-occurrence of sleep problems and AUD. We have previously shown that mice lacking ENT1 (ENT1 KO) have reduced adenosine levels in the striatum and drink more alcohol compared with wild types (WT). However, it is unknown whether ENT1 deletion disrupts circadian rhythms, which may contribute to alcohol preference in ENT1 KO mice. Here we used these mice to determine whether endogenous adenosine regulates circadian genetic and behavioral rhythms and influences alcohol intake during chronodisruption. We examined circadian locomotor activity in ENT1 KO vs WT littermates and found that ENT1 KO mice were both active earlier and hyperactive compared with WT mice at night. We used real-time PCR and immunohistochemistry to estimate striatal clock gene levels and found that PER2 expression in the striatum was blunted by ENT1 deletion or A2A receptor (A2AR) antagonism. Next, we exposed ENT1 KO and WT mice to constant light (LL) and found further elevation in ethanol intake in ENT1 KO, but not in WT mice, supporting the notion that circadian dysfunction may contribute to increased alcohol intake in ENT1 KO mice. Finally, we showed that A2AR agonist administration normalized PER1 and PER2 expression and circadian locomotor activity in ENT1 KO mice. Together, our results demonstrate that adenosine signaling regulates cellular and behavioral circadian timing and influences alcohol intake during chronodisruption.

Genetic risk prediction and neurobiological understanding of alcoholism

We have used a translational Convergent Functional Genomics (CFG) approach to discover genes involved in alcoholism, by gene-level integration of genome-wide association study (GWAS) data from a German alcohol dependence cohort with other genetic and gene expression data, from human and animal model studies, similar to our previous work in bipolar disorder and schizophrenia. A panel of all the nominally significant P-value SNPs in the top candidate genes discovered by CFG  (n=135 genes, 713 SNPs) was used to generate a genetic  risk prediction score (GRPS), which showed a trend towards significance (P=0.053) in separating  alcohol dependent individuals from controls in an independent German test cohort. We then validated and prioritized our top findings from this discovery work, and subsequently tested them in three independent cohorts, from two continents. A panel of all the nominally significant P-value single-nucleotide length polymorphisms (SNPs) in the top candidate genes discovered by CFG (n=135 genes, 713 SNPs) were used to generate a Genetic Risk Prediction Score (GRPS), which showed a trend towards significance (P=0.053) in separating alcohol-dependent individuals from controls in an independent German test cohort. In order to validate and prioritize the key genes that drive behavior without some of the pleiotropic environmental confounds present in humans, we used a stress-reactive animal model of alcoholism developed by our group, the D-box binding protein (DBP) knockout mouse, consistent with the surfeit of stress theory of addiction proposed by Koob and colleagues. A much smaller panel (n=11 genes, 66 SNPs) of the top CFG-discovered genes for alcoholism, cross-validated and prioritized by this stress-reactive animal model showed better predictive ability in the independent German test cohort (P=0.041). The top CFG scoring gene for alcoholism from the initial discovery step, synuclein alpha (SNCA) remained the top gene after the stress-reactive animal model cross-validation. We also tested this small panel of genes in two other independent test cohorts from the United States, one with alcohol dependence (P=0.00012) and one with alcohol abuse (a less severe form of alcoholism; P=0.0094). SNCA by itself was able to separate alcoholics from controls in the alcohol-dependent cohort (P=0.000013) and the alcohol abuse cohort (P=0.023). So did eight other genes from the panel of 11 genes taken individually, albeit to a lesser extent and/or less broadly across cohorts. SNCA, GRM3 and MBP survived strict Bonferroni correction for multiple comparisons. Taken together, these results suggest that our stress-reactive DBP animal model helped to validate and prioritize from the CFG-discovered genes some of the key behaviorally relevant genes for alcoholism. These genes fall into a series of biological pathways involved in signal transduction, transmission of nerve impulse (including myelination) and cocaine addiction. Overall, our work provides leads towards a better understanding of illness, diagnostics and therapeutics, including treatment with omega-3 fatty acids. We also examined the overlap between the top candidate genes for alcoholism from this work and the top candidate genes for bipolar disorder, schizophrenia, anxiety from previous CFG analyses conducted by us, as well as cross-tested genetic risk predictions. This revealed the significant genetic overlap with other major psychiatric disorder domains, providing a basis for comorbidity and dual diagnosis, and placing alcohol use in the broader context of modulating the mental landscape.

Identifying Genetic Variants for Addiction via Propensity Score Adjusted Generalized Kendall's Tau

Identifying replicable genetic variants for addiction has been extremely challenging. Besides the common difficulties with genome-wide association studies (GWAS), environmental factors are known to be critical to addiction, and comorbidity is widely observed. Despite the importance of environmental factors and comorbidity for addiction study, few GWAS analyses adequately considered them due to the limitations of the existing statistical methods. Although parametric methods have been developed to adjust for covariates in association analysis, difficulties arise when the traits are multivariate because there is no ready-to-use model for them. Recent nonparametric development includes U-statistics to measure the phenotype-genotype association weighted by a similarity score of covariates. However, it is not clear how to optimize the similarity score. Therefore, we propose a semiparametric method to measure the association adjusted by covariates. In our approach, the nonparametric U-statistic is adjusted by parametric estimates of propensity scores using the idea of inverse probability weighting. The new measurement is shown to be asymptotically unbiased under our null hypothesis while the previous non-weighted and weighted ones are not. Simulation results show that our test improves power as opposed to the non-weighted and two other weighted U-statistic methods, and it is particularly powerful for detecting gene-environment interactions. Finally, we apply our proposed test to the Study of Addiction: Genetics and Environment (SAGE) to identify genetic variants for addiction. Novel genetic variants are found from our analysis, which warrant further investigation in the future.

Diurnal rodents as an advantageous model for affective disorders: novel data from diurnal degu (Octodon degus)

Circadian rhythms are strongly associated with affective disorders and recent studies have suggested utilization of diurnal rodents as model animal for circadian rhythms-related domains of these disorders. Previous work with the diurnal fat sand rat and Nile grass rat demonstrated that short photoperiod conditions result in behavioral changes including anxiety- and depression-like behavior. The present study examined the effect of manipulating day length on activity rhythms and behavior of the diurnal degu. Animals were housed for 3 weeks under either a short photoperiod (5-h:19-h LD) or a neutral photoperiod (12-h:12-h LD) and then evaluated by sweet solution test and the forced swim test for depression-like behavior, and in the light/dark box and open field for anxiety-like behavior. Results indicate that short photoperiod induced depression-like behavior in the forced swim test and the sweet solution preference test and anxiety-like behavior in the open field compared with animals maintained in a neutral photoperiod. No effects were shown in the light/dark box. Short photoperiod-acclimated degu showed reduced total activity duration and activity was not restricted to the light phase. The present study further supports the utilization of diurnal rodents to model circadian rhythms-related affective change. Beyond the possible diversity in the mechanisms underlying diurnality in different animals, there are now evidences that in three different diurnal species, the fat sand rat, the grass Nile rat and the degu, shortening of photoperiod results in the appearance of anxiety- and depression-like behaviors.

Shared genetic factors influence risk for bipolar disorder and alcohol use disorders

Bipolar disorder and alcohol use disorder (AUD) have a high rate of comorbidity, more than 50% of individuals with bipolar disorder also receive a diagnosis of AUD in their lifetimes. Although both disorders are heritable, it is unclear if the same genetic factors mediate risk for bipolar disorder and AUD. We examined 733 Costa Rican individuals from 61 bipolar pedigrees. Based on a best estimate process, 32% of the sample met criteria for bipolar disorder, 17% had a lifetime AUD diagnosis, 32% met criteria for lifetime nicotine dependence, and 21% had an anxiety disorder. AUD, nicotine dependence and anxiety disorders were relatively more common among individuals with bipolar disorder than in their non-bipolar relatives. All illnesses were shown to be heritable and bipolar disorder was genetically correlated with AUD, nicotine dependence and anxiety disorders. The genetic correlation between bipolar and AUD remained when controlling for anxiety, suggesting that unique genetic factors influence the risk for comorbid bipolar and AUD independent of anxiety. Our findings provide evidence for shared genetic effects on bipolar disorder and AUD risk. Demonstrating that common genetic factors influence these independent diagnostic constructs could help to refine our diagnostic nosology.

Discovery and validation of blood biomarkers for suicidality

Suicides are a leading cause of death in psychiatric patients, and in society at large. Developing more quantitative and objective ways (biomarkers) for predicting and tracking suicidal states would have immediate practical applications and positive societal implications. We undertook such an endeavor. First, building on our previous blood biomarker work in mood disorders and psychosis, we decided to identify blood gene expression biomarkers for suicidality, looking at differential expression of genes in the blood of subjects with a major mood disorder (bipolar disorder), a high-risk population prone to suicidality. We compared no suicidal ideation (SI) states and high SI states using a powerful intrasubject design, as well as an intersubject case-case design, to generate a list of differentially expressed genes. Second, we used a comprehensive Convergent Functional Genomics (CFG) approach to identify and prioritize from the list of differentially expressed gene biomarkers of relevance to suicidality. CFG integrates multiple independent lines of evidence-genetic and functional genomic data-as a Bayesian strategy for identifying and prioritizing findings, reducing the false-positives and false-negatives inherent in each individual approach. Third, we examined whether expression levels of the blood biomarkers identified by us in the live bipolar subject cohort are actually altered in the blood in an age-matched cohort of suicide completers collected from the coroner's office, and report that 13 out of the 41 top CFG scoring biomarkers (32%) show step-wise significant change from no SI to high SI states, and then to the suicide completers group. Six out of them (15%) remained significant after strict Bonferroni correction for multiple comparisons. Fourth, we show that the blood levels of SAT1 (spermidine/spermine N1-acetyltransferase 1), the top biomarker identified by us, at the time of testing for this study, differentiated future as well as past hospitalizations with suicidality, in a live cohort of bipolar disorder subjects, and exhibited a similar but weaker pattern in a live cohort of psychosis (schizophrenia/schizoaffective disorder) subjects. Three other (phosphatase and tensin homolog (PTEN), myristoylated alanine-rich protein kinase C substrate (MARCKS), and mitogen-activated protein kinase kinase kinase 3 (MAP3K3)) of the six biomarkers that survived Bonferroni correction showed similar but weaker effects. Taken together, the prospective and retrospective hospitalization data suggests SAT1, PTEN, MARCKS and MAP3K3 might be not only state biomarkers but trait biomarkers as well. Fifth, we show how a multi-dimensional approach using SAT1 blood expression levels and two simple visual-analog scales for anxiety and mood enhances predictions of future hospitalizations for suicidality in the bipolar cohort (receiver-operating characteristic curve with area under the curve of 0.813). Of note, this simple approach does not directly ask about SI, which some individuals may deny or choose not to share with clinicians. Lastly, we conducted bioinformatic analyses to identify biological pathways, mechanisms and medication targets. Overall, suicidality may be underlined, at least in part, by biological mechanisms related to stress, inflammation and apoptosis.

Convergent functional genomics of psychiatric disorders

Genetic and gene expression studies, in humans and animal models of psychiatric and other medical disorders, are becoming increasingly integrated. Particularly for genomics, the convergence and integration of data across species, experimental modalities and technical platforms is providing a fit-to-disease way of extracting reproducible and biologically important signal, in contrast to the fit-to-cohort effect and limited reproducibility of human genetic analyses alone. With the advent of whole-genome sequencing and the realization that a major portion of the non-coding genome may contain regulatory variants, Convergent Functional Genomics (CFG) approaches are going to be essential to identify disease-relevant signal from the tremendous polymorphic variation present in the general population. Such work in psychiatry can provide an example of how to address other genetically complex disorders, and in turn will benefit by incorporating concepts from other areas, such as cancer, cardiovascular diseases, and diabetes.

Convergent functional genomics of stem cell-derived cells

Stem cell technologies provide an exciting avenue to directly access the transcriptome of patients in neuronal-like cell types, which might have more direct relevance to brain research than other peripheral tissues (blood, fibroblasts). Enthusiasm should be tempered by concerns that artifacts and noise might be generated as part of the in vitro process of creating and maintaining these cell type. A solution may be to apply a Convergent Functional Genomics approach, where the data from stem cell-derived neuronal cells are integrated, cross-validated and prioritized using independent lines of evidence from other approaches and platforms (human genetic data, human postmortem brain data, animal model data). I provide a brief overview and an example in support of such an approach.

Genetic variation in the alpha synuclein gene (SNCA) is associated with BOLD response to alcohol cues

OBJECTIVE

Preclinical studies implicate the gene encoding the alpha synuclein protein (SNCA) in the pathophysiology of alcohol dependence and dopamine neuron function. Results from clinical studies are less conclusive. Using neurobiological phenotypes in genetic studies, rather than typical heterogeneous diagnostic categories derived from self-report, may improve reliability across studies. This study aimed to examine whether polymorphisms in the SNCA gene were associated with alcohol taste cue-elicited responses in the brain, one such intermediate phenotype.

METHOD

A total of 326 heavy drinkers who underwent an alcohol taste task during functional magnetic resonance imaging (fMRI) also were genotyped. Analyses focused on two previously identified SNCA variants (rs2583985 and rs356168) as well as 27 other single nucleotide polymorphisms from the Illumina Human1M BeadChip that were used in an exploratory analysis of the whole gene. Neurobiological phenotypes were defined as fMRI blood oxygenation level-dependent (BOLD) responses to alcohol taste cue (vs. a control cue) in seven regions of interest known to be involved in cue processing and rich in dopaminergic axon terminals.

RESULTS

Polymorphisms in the SNCA gene were significantly correlated with BOLD activation. Specifically, the largest effect sizes and significance were seen for rs2583985 in paracingulate and caudate (focused analysis) and for rs1372522 in paracingulate (exploratory analysis). Activation in all regions of interest was correlated with alcohol-dependence severity.

CONCLUSIONS

SNCA genotype was found to be associated with the degree of fMRI BOLD response during exposure to the taste of alcohol versus a control taste. This study also further validates the use of this alcohol taste task as an intermediate phenotype for alcohol-dependence severity.

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.

Chronic valproate attenuates some, but not all, facets of mania-like behaviour in mice

Bipolar disorder (BD) mania is a psychiatric disorder with multifaceted symptoms. Development of targeted treatments for BD mania may benefit from animal models that mimic multiple symptoms, as opposed to hyperactivity alone. Using the reverse-translated multivariate exploratory paradigm, the behavioural pattern monitor (BPM), we reported that patients with BD mania exhibit hyperactivity as well as increased specific exploration and more linear movements through space. This abnormal profile is also observed in mice with reduced function of the dopamine transporter (DAT) through either constitutive genetic [knockdown (KD)] or acute pharmacological (GBR12909) means. Here, we assessed the pharmacological predictive validity of these models by administering the BD-treatment valproic acid (VPA) for 28 d. After 1.5% VPA- or regular-chow treatment for 28 d, C57BL/6J mice received GBR12909 (9 mg/kg) or saline and were tested in the BPM. Similarly, DAT KD and wild type (WT) littermates were treated with VPA-chow and tested in the BPM. GBR12909-treated and DAT KD mice on regular chow were hyperactive, exhibited increased specific exploration and moved in straighter patterns compared to saline-treated and WT mice respectively. Chronic 1.5% VPA-chow treatment resulted in therapeutic concentrations of VPA and ameliorated hyperactivity in both models, while specific exploration and behavioural organization remained unaffected. Hence, the mania-like profile of mice with reduced functional DAT was partially attenuated by chronic VPA treatment, consistent with the incomplete symptomatic effect of VPA treatment in BD patients. Both DAT models may help to identify therapeutics that impact the full spectrum of BD mania.

The ANK3 bipolar disorder gene regulates psychiatric-related behaviors that are modulated by lithium and stress

BACKGROUND

Ankyrin 3 (ANK3) has been strongly implicated as a risk gene for bipolar disorder (BD) by recent genome-wide association studies of patient populations. However, the genetic variants of ANK3 contributing to BD risk and their pathological function are unknown.

METHODS

To gain insight into the potential disease relevance of ANK3, we examined the function of mouse Ank3 in the regulation of psychiatric-related behaviors using genetic, neurobiological, pharmacological, and gene-environment interaction (G×E) approaches. Ank3 expression was reduced in mouse brain either by viral-mediated RNA interference or through disruption of brain-specific Ank3 in a heterozygous knockout mouse.

RESULTS

RNA interference of Ank3 in hippocampus dentate gyrus induced a highly specific and consistent phenotype marked by decreased anxiety-related behaviors and increased activity during the light phase, which were attenuated by chronic treatment with the mood stabilizer lithium. Similar behavioral alterations of reduced anxiety and increased motivation for reward were also exhibited by Ank3+/- heterozygous mice compared with wild-type Ank3+/+ mice. Remarkably, the behavioral traits of Ank3+/- mice transitioned to depression-related features after chronic stress, a trigger of mood episodes in BD. Ank3+/- mice also exhibited elevated serum corticosterone, suggesting that reduced Ank3 expression is associated with elevated stress reactivity.

CONCLUSIONS

This study defines a new role for Ank3 in the regulation of psychiatric-related behaviors and stress reactivity that lends support for its involvement in BD and establishes a general framework for determining the disease relevance of genes implicated by patient genome-wide association studies.

Rodent models for mania: practical approaches

The scarcity of good animal models for bipolar disorder (BPD) and especially for mania is repeatedly mentioned as one of the rate-limiting factors in the process of gaining a better understanding into its pathophysiology and of developing better treatments. Standard models of BPD have some value but usually represent only one facet of the disease and have partial validity. A number of new approaches for modeling BPD and specifically mania have been suggested in the last few years and can be combined to improve models. These approaches include targeted mutation models representing reverse translation, the identification of advantageous strains for components of the disorder, a search for the most homologous species to address specific human pathology, and the exploration of individual differences of response including the separation between susceptible and resilient animals. Additionally, recent efforts have identified and developed new tests to distinguish between "normal" and "BPD-like" animals including the different utilization of known tests and novel tests such as the female-urine-sniffing test and behavior pattern monitor analysis. Additional tests relating to further domains of BPD are still needed. An ideal model for BPD that will encompass the entire disease and be useful for every demand will probably not become available until we have a full understanding of the pathophysiology of the disorder. However, the current advances in modeling should lead to better comprehension of the disorder and therefore to the gradual development of increasingly improved models.

Analysis of region-specific changes in gene expression upon treatment with citalopram and desipramine reveals temporal dynamics in response to antidepressant drugs at the transcriptome level

RATIONALE

The notion that the onset of action of antidepressant drugs (ADs) takes weeks is widely accepted; however, the sequence of events necessary for therapeutic effects still remains obscure.

OBJECTIVE

We aimed to evaluate a time-course of ADs-induced alterations in the expression of 95 selected genes in 4 regions of the rat brain: the prefrontal and cingulate cortices, the dentate gyrus of the hippocampus, and the amygdala.

METHODS

We employed RT-PCR array to evaluate changes during a time-course (1, 3, 7, 14, and 21 days) of treatments with desipramine (DMI) and citalopram (CIT). In addition to repeated treatment, we also conducted acute treatment (a single dose of drug followed by the same time intervals as the repeated doses).

RESULTS

Time-dependent and structure-specific changes in gene expression patterns allowed us to identify spatiotemporal differences in the molecular action of two ADs. Singular value decomposition analysis revealed differences in the global gene expression profiles between treatment types. The numbers of characteristic modes were generally smaller after CIT treatment than after DMI treatment. Analysis of the dynamics of gene expression revealed that the most significant changes concerned immediate early genes, whose expression was also visualized by in situ hybridization. Transcription factor binding site analysis revealed an over-representation of serum response factor binding sites in the promoters of genes that changed upon treatment with both ADs.

CONCLUSIONS

The observed gene expression patterns were highly dynamic, with oscillations and peaks at various time points of treatment. Our study also revealed novel potential targets of antidepressant action, i.e., Dbp and Id1 genes.