CRY2 Genetic Variants Associate with Dysthymia

People with mood disorders often have disruptions in their circadian rhythms. Recent molecular genetics has linked circadian clock genes to mood disorders. Our objective was to study two core circadian clock genes, CRY1 and CRY2 as well as TTC1 that interacts with CRY2, in relation to depressive and anxiety disorders. Of these three genes, 48 single-nucleotide polymorphisms (SNPs) whose selection was based on the linkage disequilibrium and potential functionality were genotyped in 5910 individuals from a nationwide population-based sample. The diagnoses of major depressive disorder, dysthymia and anxiety disorders were assessed with a structured interview (M-CIDI). In addition, the participants filled in self-report questionnaires on depressive and anxiety symptoms. Logistic and linear regression models were used to analyze the associations of the SNPs with the phenotypes. Four CRY2 genetic variants (rs10838524, rs7121611, rs7945565, rs1401419) associated significantly with dysthymia (false discovery rate q<0.05). This finding together with earlier CRY2 associations with winter depression and with bipolar type 1 disorder supports the view that CRY2 gene has a role in mood disorders.     

Analysis of TBX1 variation in patients with psychotic and affective disorders

A significant portion of patients with 22q11 deletion syndrome (22q11DS) develop psychiatric disorders, including schizophrenia and other psychotic and affective symptoms, and the responsible gene/s are assumed to also play a significant role in the etiology of nonsyndromic psychiatric disease. The most common psychiatric diagnosis among patients with 22q11DS is schizophrenia, thought to result from neurotransmitter imbalances and also from disturbed brain development. Several genes in the 22q11 region with known or suspected roles in neurotransmitter metabolism have been analyzed in patients with isolated schizophrenia; however, their contribution to the disease remains controversial. Haploinsufficiency of the TBX1 gene has been shown to be sufficient to cause the core physical malformations associated with 22q11DS in mice and humans and via abnormal brain development could contribute to 22q11DS-related and isolated psychiatric disease. 22q11DS populations also have increased rates of psychiatric conditions other than schizophrenia, including mood disorders. We therefore analyzed variations at the TBX1 locus in a cohort of 446 white patients with psychiatric disorders relevant to 22q11DS and 436 ethnically matched controls. The main diagnoses included schizophrenia (n = 226), schizoaffective disorder (n = 67), bipolar disorder (n = 82), and major depressive disorder (n = 29). We genotyped nine tag SNPs in this sample but did not observe significant differences in allele or haplotype frequencies in any of the analyzed groups (all affected, schizophrenia and schizoaffective disorder, schizophrenia alone, and bipolar disorder and major depressive disorder) compared with the control group. Based on these results we conclude that TBX1 variation does not make a strong contribution to the genetic etiology of nonsyndromic forms of psychiatric disorders commonly seen in patients with 22q11DS.     

The CLOCK gene and mood disorders: a case-control study and meta-analysis

The clock gene (CLOCK) is considered to be a good candidate gene for the pathophysiology of mood disorders, including bipolar disorder (BP) and major depressive disorder (MDD). rs1801260 (T3111C) has been detected at position 3111 in the CLOCK mRNA 3' untranslated region, and was reported to be associated with a substantial delay in preferred timing for activity and sleep in a human study. As for function, rs1801260 has been speculated to affect mRNA. Therefore, the authors investigated the association between the three tagging single-nucleotide polymorphisms (SNPs) (rs3736544, rs1801260, and rs3749474) in CLOCK and risk of BP (n=867) and MDD (n=139) compared to controls (n=889) in the Japanese population. In addition, we also performed an updated meta-analysis of nine published, genetic association studies investigating the relationship between rs1801260 and mood disorder risk, comprising 3321 mood disorders cases and 3574 controls. We did not detect any associations between tagging SNPs in CLOCK and BP or MDD in the allele, genotype, or haplotype analysis (global p(BP)=.605 and global p(MDD)=.211). Moreover, rs1801260 was also not associated with BP, MDD, or any mood disorders in the meta-analysis. In conclusion, these data suggest that CLOCK does not play a major role in the pathophysiology of mood disorders.     

Chronic Treatment with Anti-bipolar Drugs Causes Intracellular Alkalinization in Astrocytes,Altering Their Functions

Neurochemical Research - Bipolar disorder I and II are affective disorders with mood changes between depressive and manic (bipolar I) or hypomanic (bipolar II) periods. Current therapy of these...     

The CLOCK Gene and Mood Disorders: A Case-Control Study and Meta-analysis

The clock gene (CLOCK) is considered to be a good candidate gene for the pathophysiology of mood disorders, including bipolar disorder (BP) and major depressive disorder (MDD). rs1801260 (T3111C) has been detected at position 3111 in the CLOCK mRNA 3' untranslated region, and was reported to be associated with a substantial delay in preferred timing for activity and sleep in a human study. As for function, rs1801260 has been speculated to affect mRNA. Therefore, the authors investigated the association between the three tagging single-nucleotide polymorphisms (SNPs) (rs3736544, rs1801260, and rs3749474) in CLOCK and risk of BP (n?=?867) and MDD (n?=?139) compared to controls (n?=?889) in the Japanese population. In addition, we also performed an updated meta-analysis of nine published, genetic association studies investigating the relationship between rs1801260 and mood disorder risk, comprising 3321 mood disorders cases and 3574 controls. We did not detect any associations between tagging SNPs in CLOCK and BP or MDD in the allele, genotype, or haplotype analysis (global p_BP?=?.605 and global p_MDD?=?.211). Moreover, rs1801260 was also not associated with BP, MDD, or any mood disorders in the meta-analysis. In conclusion, these data suggest that CLOCK does not play a major role in the pathophysiology of mood disorders. (Author correspondence: tarok@fujita-hu.ac.jp)     

A haplotype of glycogen synthase kinase 3β is associated with early onset of unipolar major depression

Recent findings suggest that glycogen synthase kinase 3β (GSK3β) may play a role in the pathophysiology and treatment of mood disorders. Various genetic studies have shown the association of GSK3β polymorphisms with different mood disorder phenotypes. We hypothesized that genetic variants in the GSK3β gene could partially underlie the susceptibility to mood disorders. We performed a genetic case–control study of 440 psychiatrically screened control subjects and 445 mood disorder patients [256 unipolar major depressive disorder (MDD) and 189 bipolar disorder (BD)]. We genotyped a set of 11 single nucleotide polymorphisms (SNPs) and determined the relative frequency of a known copy number variant (CNV) overlapping the GSK3β by quantitative real‐time polymerase chain reaction (PCR). We found no evidence of association with MDD or BD diagnosis, and we further investigated the age at onset (AAO) of the disorder and severity of depressive index episode. We found that rs334555, located in intron 1 of GSK3β, was nominally associated with an earlier AAO of the disease in MDD (P = 0.001). We also identified a haplotype containing three SNPs (rs334555, rs119258668 and rs11927974) associated with AAO of the disorder (permutated P = 0.0025). We detected variability for the CNV, but we could not detect differences between patients and controls for any of the explored phenotypes. This study presents further evidence of the contribution of GSK3β to mood disorders, implicating a specific SNP and a haplotype with an earlier onset of the disorder in a group of well‐characterized patients with unipolar MDD. Further replication studies in patients with the same phenotypic characteristics should confirm the results reported here.     

Mitochondria,endoplasmic reticulum and innate immune dysfunction in mood disorders: Do Mitochondria-Associated Membranes (MAMs) play a role?

Mood disorders like major depression and bipolar disorder (BD) are among the most prevalent forms of mental illness. Current knowledge of the neurobiology and pathophysiology of these disorders is still modest and clear biological markers are still missing. Thus, a better understanding of the underlying pathophysiological mechanisms to identify potential therapeutic targets is a prerequisite for the design of new drugs as well as to develop biomarkers that help in a more accurate and earlier diagnosis.Multiple pieces of evidence including genetic and neuro-imaging studies suggest that mood disorders are associated with abnormalities in endoplasmic-reticulum (ER)-related stress responses, mitochondrial function and calcium signalling. Furthermore, deregulation of the innate immune response has been described in patients diagnosed with mood disorders, including depression and BD. These disease-related events are associated with functions localized to a subdomain of the ER, known as Mitochondria-Associated Membranes (MAMs), which are lipid rafts-like domains that connect mitochondria and ER, both physically and biochemically.This review will outline the current understanding of the role of mitochondria and ER dysfunction under pathological brain conditions, particularly in major depressive disorder (MDD) and BD, that support the hypothesis that MAMs can act in these mood disorders as the link connecting ER-related stress response and mitochondrial impairment, as well as a mechanisms behind sterile inflammation arising from deregulation of innate immune responses. The role of MAMs in the pathophysiology of these pathologies and its potential relevance as a potential therapeutic target will be discussed.     

Genome wide gene expression studies in mood disorders

Microarrays offer the possibility of screening in parallel virtually all genes expressed in a given tissue or to study the molecular signature associated with available treatments. As such, this technology has been increasingly used to investigate multifactorial and polygenic complex traits such as psychiatric disorders, in particular, schizophrenia and mood disorders. This review focuses on microarray studies investigating mood disorders. Study designs, methodologic approaches and limitations, subsequent follow-up strategies, and confirmation of results are discussed. Despite the apparent disparate and not always concordant results, it appears evident that this technology is a powerful and inevitable approach for the study of mood disorders, especially when phenotype-specific confounders are properly accounted for. Thus, alterations of mitochondrial, oligodendrocyte, and myelin related genes in bipolar disorder, of signaling and olidendroglial related genes in depression, and of GABA-glutamate related genes in depression and suicide have been observed and have confirmed new avenues for the study and the treatment of these complex disorders.     

Effects of antipsychotics,antidepressants and mood stabilizers on risk for physical diseases in people with schizophrenia,depression and bipolar disorder

People with severe mental illness have a considerably shorter lifespan than the general population. This excess mortality is mainly due to physical illness. Next to mental illness‐related factors, unhealthy lifestyle, and disparities in health care access and utilization, psychotropic medications can contribute to the risk of physical morbidity and mortality. We systematically reviewed the effects of antipsychotics, antidepressants and mood stabilizers on physical health outcomes in people with schizophrenia, depression and bipolar disorder. Updating and expanding our prior systematic review published in this journal, we searched MEDLINE (November 2009 ‐ November 2014), combining the MeSH terms of major physical disease categories (and/or relevant diseases within these categories) with schizophrenia, major depressive disorder and bipolar disorder, and the three major psychotropic classes which received regulatory approval for these disorders, i.e., antipsychotics, antidepressants and mood stabilizers. We gave precedence to results from (systematic) reviews and meta‐analyses wherever possible. Antipsychotics, and to a more restricted degree antidepressants and mood stabilizers, are associated with an increased risk for several physical diseases, including obesity, dyslipidemia, diabetes mellitus, thyroid disorders, hyponatremia; cardiovascular, respiratory tract, gastrointestinal, haematological, musculoskeletal and renal diseases, as well as movement and seizure disorders. Higher dosages, polypharmacy, and treatment of vulnerable (e.g., old or young) individuals are associated with greater absolute (elderly) and relative (youth) risk for most of these physical diseases. To what degree medication‐specific and patient‐specific risk factors interact, and how adverse outcomes can be minimized, allowing patients to derive maximum benefits from these medications, requires adequate clinical attention and further research.     

Nonlinear time-series approaches in characterizing mood stability and mood instability in bipolar disorder

Bipolar disorder is a psychiatric condition characterized by episodes of elevated mood interspersed with episodes of depression. While treatment developments and understanding the disruptive nature of this illness have focused on these episodes, it is also evident that some patients may have chronic week-to-week mood instability. This is also a major morbidity. The longitudinal pattern of this mood instability is poorly understood as it has, until recently, been difficult to quantify. We propose that understanding this mood variability is critical for the development of cognitive neuroscience-based treatments. In this study, we develop a time-series approach to capture mood variability in two groups of patients with bipolar disorder who appear on the basis of clinical judgement to show relatively stable or unstable illness courses. Using weekly mood scores based on a self-rated scale (quick inventory of depressive symptomatology-self-rated; QIDS-SR) from 23 patients over a 220-week period, we show that the observed mood variability is nonlinear and that the stable and unstable patient groups are described by different nonlinear time-series processes. We emphasize the necessity in combining both appropriate measures of the underlying deterministic processes (the QIDS-SR score) and noise (uncharacterized temporal variation) in understanding dynamical patterns of mood variability associated with bipolar disorder.     

Sleep,daily activity rhythms and postpartum mood: A longitudinal study across the perinatal period

Women with a diagnosis of bipolar and major depressive disorders are at higher risk to develop postpartum depression. The primary objective of this longitudinal study was to determine whether daily activity rhythms and sleep parameters differ between women with and without a history of a mood disorder across the perinatal period. A secondary objective was to determine whether changes in these parameters were associated with postpartum mood. In total, 33 women were included in this study, 15 of which had a history of a mood disorder (high-risk group) and 18 who did not (low-risk group). Sleep and daily rhythms were assessed subjectively and objectively during the third trimester (≥26 weeks gestation) and again at 6–12 weeks postpartum. Mood was also assessed at both time points. Women in the high-risk group showed greater subjective daily rhythms and sleep disturbances across the perinatal period. Objective sleep efficiency was worse in the high-risk group in the postpartum period. Changes in both subjective daily rhythms and objective sleep efficiency were predictive of changes in depressive symptoms across the perinatal period. These findings encourage the development of preventative therapeutics to ensure circadian rhythm and sleep stability throughout the perinatal period.     

Integrating GWASs and Human Protein Interaction Networks Identifies a Gene Subnetwork Underlying Alcohol Dependence

Despite a significant genetic contribution to alcohol dependence (AD), few AD-risk genes have been identified to date. In the current study, we aimed to integrate genome-wide association studies (GWASs) and human protein interaction networks to investigate whether a subnetwork of genes whose protein products interact with one another might collectively contribute to AD. By using two discovery GWAS data sets of the Study of Addiction: Genetics and Environment (SAGE) and the Collaborative Study on the Genetics of Alcoholism (COGA), we identified a subnetwork of 39 genes that not only was enriched for genes associated with AD, but also collectively associated with AD in both European Americans (p < 0.0001) and African Americans (p = 0.0008). We replicated the association of the gene subnetwork with AD in three independent samples, including two samples of European descent (p = 0.001 and p = 0.006) and one sample of African descent (p = 0.0069). To evaluate whether the significant associations are likely to be false-positive findings and to ascertain their specificity, we examined the same gene subnetwork in three other human complex disorders (bipolar disorder, major depressive disorder, and type 2 diabetes) and found no significant associations. Functional enrichment analysis revealed that the gene subnetwork was enriched for genes involved in cation transport, synaptic transmission, and transmission of nerve impulses, all of which are biologically meaningful processes that may underlie the risk for AD. In conclusion, we identified a gene subnetwork underlying AD that is biologically meaningful and highly reproducible, providing important clues for future research into AD etiology and treatment.     

Proteomic analysis of the anterior cingulate cortex in the major psychiatric disorders: Evidence for disease-associated changes

Abnormalities of the anterior cingulate cortex have previously been described in schizophrenia, major depressive disorder and bipolar disorder. In this study 2-DE was performed followed by mass spectrometric sequencing to identify disease-specific protein changes within the anterior cingulate cortex in these psychiatric disorders. The 2-DE system comprised IPGs 4-7 and 6-9 in the first, IEF dimension and SDS-PAGE in the second dimension. Resultant protein spots were compared between control and disease groups. Statistical analysis indicated that 35 spots were differentially expressed in one or more groups. Proteins comprising 26 of these spots were identified by mass spectroscopy. These represented 19 distinct proteins; aconitate hydratase, malate dehydrogenase, fructose bisphosphate aldolase A, ATP synthase, succinyl CoA ketoacid transferase, carbonic anhydrase, alpha- and beta-tubulin, dihydropyrimidinase-related protein-1 and -2, neuronal protein 25, trypsin precursor, glutamate dehydrogenase, glutamine synthetase, sorcin, vacuolar ATPase, creatine kinase, albumin and guanine nucleotide binding protein beta subunit. All but three of these proteins have previously been associated with the major psychiatric disorders. These findings provide support for the view that cytoskeletal and mitochondrial dysfunction are important components of the neuropathology of the major psychiatric disorders.     

The Compensatory Immune-Regulatory Reflex System (CIRS) in Depression and Bipolar Disorder

Here, we review a novel concept namely the compensatory immune-regulatory reflex system (CIRS) as applied to the pathophysiology of major depressive disorder (MDD) and bipolar disorder (BD). There is evidence that a substantial subset of individuals with MDD and BD exhibit an activation of the immune-inflammatory response system (IRS), as indicated by an increased production of macrophagic M1 and T helper (Th)-1 pro-inflammatory cytokines, interleukin (IL)-6 trans-signaling, positive acute phase proteins (APPs), and complement factors. These immune aberrations appear to be evident during the course of major affective episodes of either depressive or (hypo) manic polarity. Here, we review (a) the current state of the art of CIRS functions in both mood disorders and (b) the possible role of CIRS-related biomarkers for the understanding of affective disorders within the framework of precision psychiatry that could also provide novel drug targets for both MDD and BD. CIRS-related abnormalities in mood disorders include elevated Th-2 and T regulatory (Treg) activities with increased IL-4 and IL-10 production, classical IL-6 signaling, increased levels of sIL-1R antagonist (sIL-1RA), soluble IL-2 (sIL-2R) and tumor necrosis factor–α- receptors, and positive APPs, including haptoglobin, hemopexin, α1-acid glycoprotein, α1-antitrypsin, and ceruloplasmin. It is concluded that CIRS is involved in MDD and BD by regulating the primary immune-inflammatory response, thereby contributing to spontaneous and antidepressant-promoted recovery from the acute phase of illness. Signs of activated IRS and CIRS pathways are observed in the remitted phases of both disorders indicating that there is no return to the original homeostasis after an acute episode, while later episodes of mood disorders are characterized by sensitized IRS and CIRS responses. New z-unit weighted composite biomarker scores are proposed, which reflect different aspects of IRS versus CIRS activation and may be used to estimate different IRS/CIRS activity ratios in mood and other neuroimmune disorders.     

Finding the intracellular signaling pathways affected by mood disorder treatments

Postmortem and brain imaging studies have revealed structural changes and cell loss in cortico-limbic regions of the brain in bipolar disorder and major depression. Consistent with these findings, mood stabilizers such as lithium ion and valproic acid, which are used to treat bipolar disorder, as well as antidepressants and electroconvulsive therapy have recently been shown to activate interconnected intracellular signaling pathways that promote neurogenesis and synaptic plasticity. These insights should assist in understanding the pathophysiology of severe mood disorders as well as aid in the development of more effective treatments.     

Multi-scale motility amplitude associated with suicidal thoughts in major depression

Major depression occurs at high prevalence in the general population, often starts in juvenile years, recurs over a lifetime, and is strongly associated with disability and suicide. Searches for biological markers in depression may have been hindered by assuming that depression is a unitary and relatively homogeneous disorder, mainly of mood, rather than addressing particular, clinically crucial features or diagnostic subtypes. Many studies have implicated quantitative alterations of motility rhythms in depressed human subjects. Since a candidate feature of great public-health significance is the unusually high risk of suicidal behavior in depressive disorders, we studied correlations between a measure (vulnerability index [VI]) derived from multi-scale characteristics of daily-motility rhythms in depressed subjects (n?=?36) monitored with noninvasive, wrist-worn, electronic actigraphs and their self-assessed level of suicidal thinking operationalized as a wish to die. Patient-subjects had a stable clinical diagnosis of bipolar-I, bipolar-II, or unipolar major depression (n?=?12 of each type). VI was associated inversely with suicidal thinking (r?=?-0.61 with all subjects and r?=?-0.73 with bipolar disorder subjects; both p<0.0001) and distinguished patients with bipolar versus unipolar major depression with a sensitivity of 91.7% and a specificity of 79.2%. VI may be a useful biomarker of characteristic features of major depression, contribute to differentiating bipolar and unipolar depression, and help to detect risk of suicide. An objective biomarker of suicide-risk could be advantageous when patients are unwilling or unable to share suicidal thinking with clinicians.     

A Genetic Deconstruction of Neurocognitive Traits in Schizophrenia and Bipolar Disorder

Background

Impairments in cognitive functions are common in patients suffering from psychiatric disorders, such as schizophrenia and bipolar disorder. Cognitive traits have been proposed as useful for understanding the biological and genetic mechanisms implicated in cognitive function in healthy individuals and in the dysfunction observed in psychiatric disorders.

Methods

Sets of genes associated with a range of cognitive functions often impaired in schizophrenia and bipolar disorder were generated from a genome-wide association study (GWAS) on a sample comprising 670 healthy Norwegian adults who were phenotyped for a broad battery of cognitive tests. These gene sets were then tested for enrichment of association in GWASs of schizophrenia and bipolar disorder. The GWAS data was derived from three independent single-centre schizophrenia samples, three independent single-centre bipolar disorder samples, and the multi-centre schizophrenia and bipolar disorder samples from the Psychiatric Genomics Consortium.

Results

The strongest enrichments were observed for visuospatial attention and verbal abilities sets in bipolar disorder. Delayed verbal memory was also enriched in one sample of bipolar disorder. For schizophrenia, the strongest evidence of enrichment was observed for the sets of genes associated with performance in a colour-word interference test and for sets associated with memory learning slope.

Conclusions

Our results are consistent with the increasing evidence that cognitive functions share genetic factors with schizophrenia and bipolar disorder. Our data provides evidence that genetic studies using polygenic and pleiotropic models can be used to link specific cognitive functions with psychiatric disorders.     

Bipolar I disorder and schizophrenia: a 440-single-nucleotide polymorphism screen of 64 candidate genes among Ashkenazi Jewish case-parent trios

Bipolar, schizophrenia, and schizoaffective disorders are common, highly heritable psychiatric disorders, for which familial coaggregation, as well as epidemiological and genetic evidence, suggests overlapping etiologies. No definitive susceptibility genes have yet been identified for any of these disorders. Genetic heterogeneity, combined with phenotypic imprecision and poor marker coverage, has contributed to the difficulty in defining risk variants. We focused on families of Ashkenazi Jewish descent, to reduce genetic heterogeneity, and, as a precursor to genomewide association studies, we undertook a single-nucleotide polymorphism (SNP) genotyping screen of 64 candidate genes (440 SNPs) chosen on the basis of previous linkage or of association and/or biological relevance. We genotyped an average of 6.9 SNPs per gene, with an average density of 1 SNP per 11.9 kb in 323 bipolar I disorder and 274 schizophrenia or schizoaffective Ashkenazi case-parent trios. Using single-SNP and haplotype-based transmission/disequilibrium tests, we ranked genes on the basis of strength of association (P<.01). Six genes (DAO, GRM3, GRM4, GRIN2B, IL2RB, and TUBA8) met this criterion for bipolar I disorder; only DAO has been previously associated with bipolar disorder. Six genes (RGS4, SCA1, GRM4, DPYSL2, NOS1, and GRID1) met this criterion for schizophrenia or schizoaffective disorder; five replicate previous associations, and one, GRID1, shows a novel association with schizophrenia. In addition, six genes (DPYSL2, DTNBP1, G30/G72, GRID1, GRM4, and NOS1) showed overlapping suggestive evidence of association in both disorders. These results may help to prioritize candidate genes for future study from among the many suspected/proposed for schizophrenia and bipolar disorders. They provide further support for shared genetic susceptibility between these two disorders that involve glutamate-signaling pathways.