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

Comparative genomics of macaques and integrated insights into genetic variation and population history

The crab-eating macaques ( Macaca fascicularis ) and rhesus macaques ( M. mulatta ) are widely studied nonhuman primates in biomedical and evolutionary research. Despite their significance, the current understanding of the complex genomic structure in macaques and the differences between species requires substantial improvement. Here, we present a complete genome assembly of a crab-eating macaque and 20 haplotype-resolved macaque assemblies to investigate the complex regions and major genomic differences between species. Segmental duplication in macaques is ∼42% lower, while centromeres are ∼3.7 times longer than those in humans. The characterization of ∼2 Mbp fixed genetic variants and ∼240 Mbp complex loci highlights potential associations with metabolic differences between the two macaque species (e.g., CYP2C76 and EHBP1L1 ). Additionally, hundreds of alternative splicing differences show post-transcriptional regulation divergence between these two species (e.g., PNPO ). We also characterize 91 large-scale genomic differences between macaques and humans at a single-base-pair resolution and highlight their impact on gene regulation in primate evolution (e.g., FOLH1 and PIEZO2 ). Finally, population genetics recapitulates macaque speciation and selective sweeps, highlighting potential genetic basis of reproduction and tail phenotype differences (e.g., STAB1 , SEMA3F , and HOXD13 ). In summary, the integrated analysis of genetic variation and population genetics in macaques greatly enhances our comprehension of lineage-specific phenotypes, adaptation, and primate evolution, thereby improving their biomedical applications in human diseases.

Immune, RNA, and Neurocognitive Genetic Networks in Bipolar Disorder Subtypes: A Transcriptomic Meta-Analysis

Background

Little is known about the pathogenesis of Bipolar Disorder, and even less is known about the genetic differences between its subtypes. Bipolar Disorder is classified into different subtypes, which present different symptoms and lifetime courses. While genetic studies have been conducted in Bipolar Disorder, most examined the gene expression of only Bipolar Disorder Type 1. Studies that include Bipolar Disorder Type 1 and Bipolar Disorder Type 2 often fail to differentiate them into separate conditions. Few large transcriptomic meta-analyses in Bipolar Disorder have been conducted to identify genetic pathways. Thus, using publicly available data sets we aim here to uncover significant differential gene expression that allows distinguishing Type 1 and Type 2 Bipolar Disorders, as well as find patterns in Bipolar Disorder as a whole.

Methods

We analyze 17 different gene expression data sets from different tissue in Bipolar Disorder using GEO2R and manual analysis, of which 15 contained significant differential gene expression results. We use STRING and Cytoscape to examine Gene Ontology to find significantly affected genetic pathways. We identify hub genes using cytoHubba, a plugin in Cytoscape. We find genes common to data sets of the same material or subtype.

Results

12 out of 15 data sets are enriched for immune system and RNA related pathways. 9 out of 15 data sets are enriched for neurocognitive and metal ion related GO terms. Analysis of Bipolar Disorder Type 1 vs Bipolar Disorder Type 2 revealed most differentially expressed genes were related to immune function, especially cytokines. Terms related to synaptic signaling and neurotransmitter secretion were found in down-regulated GO terms while terms related to neuron apoptosis and death were up-regulated. We identify the gene SNCA as a potential biomarker for overall Bipolar Disorder diagnosis due to its prevalence in our data sets.

Conclusions

The immune system and RNA related pathways are significantly enriched across the Bipolar Disorder data sets. The role of these pathways is likely more critically important to the function of Bipolar Disorder than currently understood. Further studies should clearly label the subtype of Bipolar Disorder used in their research and more effort needs to be undertaken to collect samples from Cyclothymic Disorder and Bipolar Disorder Type 2.

Patients with schizophrenia and bipolar disorder display a similar global gene expression signature in whole blood that reflects elevated proportion of immature neutrophil cells with association to lipid changes

Schizophrenia (SCZ) and bipolar disorder (BD) share clinical characteristics, genetic susceptibility, and immune alterations. We aimed to identify differential transcriptional patterns in peripheral blood cells of patients with SCZ or BD versus healthy controls (HC). We analyzed microarray-based global gene expression data in whole blood from a cohort of SCZ (N = 329), BD (N = 203) and HC (N = 189). In total, 65 genes were significantly differentially expressed in SCZ and 125 in BD, as compared to HC, with similar ratio of up- and downregulated genes in both disorders. Among the top differentially expressed genes, we found an innate immunity signature that was shared between SCZ and BD, consisting of a cluster of upregulated genes (e.g., OLFM4, ELANE, BPI and MPO) that indicate an increased fraction of immature neutrophils. Several of these genes displayed sex differences in the expression pattern, and post-hoc analysis demonstrated a positive correlation with triglyceride and a negative correlation with HDL cholesterol. We found that many of the downregulated genes in SCZ and BD were associated with smoking. These findings of neutrophil granulocyte-associated transcriptome signatures in both SCZ and BD point at altered innate immunity pathways with association to lipid changes and potential for clinical translation.

Dissecting the association between psychiatric disorders and neurological proteins: a genetic correlation and two-sample bidirectional Mendelian randomization study

OBJECTIVES

The role of neurological proteins in the development of bipolar disorder (BD) and schizophrenia (SCZ) remains elusive now. The current study aims to explore the potential genetic correlations of plasma neurological proteins with BD and SCZ.

METHODS

By using the latest genome-wide association study (GWAS) summary data of BD and SCZ (including 41,917 BD cases, 11,260 SCZ cases, and 396,091 controls) derived from the Psychiatric GWAS Consortium website (PGC) and a recently released GWAS of neurological proteins (including 750 individuals), we performed a linkage disequilibrium score regression (LDSC) analysis to detect the potential genetic correlations between the two common psychiatric disorders and each of the 92 neurological proteins. Two-sample Mendelian randomisation (MR) analysis was then applied to assess the bidirectional causal relationship between the neurological proteins identified by LDSC, BD and SCZ.

RESULTS

LDSC analysis identified one neurological protein, NEP, which shows suggestive genetic correlation signals for both BD (coefficient = -0.165, p value = 0.035) and SCZ (coefficient = -0.235, p value = 0.020). However, those association did not remain significant after strict Bonferroni correction. Two sample MR analysis found that there was an association between genetically predicted level of NEP protein, BD (odd ratio [OR] = 0.87, p value = 1.61 × 10^-6) and SCZ (OR = 0.90, p value = 4.04 × 10^-6). However, in the opposite direction, there is no genetically predicted association between BD, SCZ, and NEP protein level.

CONCLUSION

This study provided novel clues for understanding the genetic effects of neurological proteins on BD and SCZ.

Expression of type 1 cannabinoid receptor gene in bipolar disorder

BACKGROUND

The Endocannabinoid System (ECBs) may have a crucial role in bipolar disorder (BD). Previous reports have not detected abnormalities in the expression of the cannabinoid receptor gene CNR1, encoding for CB₁. However, we hypothesized that differentiating between mania and depression may uncover differences in CNR1 expression levels.

METHODS

We recruited 44 subjects with BD type I (BD-I), in mania (n = 22) and depression (n = 22) and 25 Healthy Controls (HC). CNR1 gene expression was analyzed using a quantitative real-time polymerase chain reaction from peripheral blood mononuclear cells. Data were analyzed using frequentist non-parametric and Bayesian approaches (generalized location-scale model based on lognormal and gamma distributions).

RESULTS

Using the frequentist non-parametric approach, the depression group had lower CNR1 expression compared to the mania group (p = 0.004). In addition, there was a negative correlation between CNR1 expression and Hamilton Depression Scale score (rho = -0.37; p = 0.007). Bayesian analyses further revealed that CNR1 expression in the mania group was higher and less variable than among HC (>95% probability), while CNR1 expression in the depression group was lower and more variable than among HC (100% probability).

LIMITATIONS

Lack of participants with bipolar disorder in the euthymic phase, lack of toxicology screening and evaluation of CNR1 variants.

CONCLUSION

CNR1 expression is higher and less variable in mania than in depression. It is highly probable that these differences also distinguish individuals in different illness phases from healthy controls. Future studies are needed to clarify the role of the endocannabinoid system in bipolar disorder.

Integrated methylome and phenome study of the circulating proteome reveals markers pertinent to brain health

Characterising associations between the methylome, proteome and phenome may provide insight into biological pathways governing brain health. Here, we report an integrated DNA methylation and phenotypic study of the circulating proteome in relation to brain health. Methylome-wide association studies of 4058 plasma proteins are performed (N = 774), identifying 2928 CpG-protein associations after adjustment for multiple testing. These are independent of known genetic protein quantitative trait loci (pQTLs) and common lifestyle effects. Phenome-wide association studies of each protein are then performed in relation to 15 neurological traits (N = 1,065), identifying 405 associations between the levels of 191 proteins and cognitive scores, brain imaging measures or APOE e4 status. We uncover 35 previously unreported DNA methylation signatures for 17 protein markers of brain health. The epigenetic and proteomic markers we identify are pertinent to understanding and stratifying brain health.

Increased levels of TAR DNA-binding protein 43 in the hippocampus of subjects with bipolar disorder: a postmortem study

Bipolar disorder shares symptoms and pathological pathways with other neurodegenerative diseases, including frontotemporal dementia (FTD). Since TAR DNA-binding protein 43 (TDP-43) is a neuropathological marker of frontotemporal dementia and it is involved in synaptic transmission, we explored the role of TDP-43 as a molecular feature of bipolar disorder (BD). Homogenates were acquired from frozen hippocampus of postmortem brains of bipolar disorder subjects. TDP-43 levels were quantified using an ELISA-sandwich method and compared between the postmortem brains of bipolar disorder subjects and age-matched control group. We found higher levels of TDP-43 protein in the hippocampus of BD (n = 15) subjects, when compared to controls (n = 15). We did not find associations of TDP-43 with age at death, postmortem interval, or age of disease onset. Our results suggest that protein TDP-43 may be potentially implicated in behavioral abnormalities seen in BD. Further investigation is needed to validate these findings and to examine the role of this protein during the disease course and mood states.

Whole blood transcriptome analysis in bipolar disorder reveals strong lithium effect

BACKGROUND

Bipolar disorder (BD) is a highly heritable mood disorder with complex genetic architecture and poorly understood etiology. Previous transcriptomic BD studies have had inconsistent findings due to issues such as small sample sizes and difficulty in adequately accounting for confounders like medication use.

METHODS

We performed a differential expression analysis in a well-characterized BD case-control sample (Nsubjects = 480) by RNA sequencing of whole blood. We further performed co-expression network analysis, functional enrichment, and cell type decomposition, and integrated differentially expressed genes with genetic risk.

RESULTS

While we observed widespread differential gene expression patterns between affected and unaffected individuals, these effects were largely linked to lithium treatment at the time of blood draw (FDR < 0.05, Ngenes = 976) rather than BD diagnosis itself (FDR < 0.05, Ngenes = 6). These lithium-associated genes were enriched for cell signaling and immune response functional annotations, among others, and were associated with neutrophil cell-type proportions, which were elevated in lithium users. Neither genes with altered expression in cases nor in lithium users were enriched for BD, schizophrenia, and depression genetic risk based on information from genome-wide association studies, nor was gene expression associated with polygenic risk scores for BD.

CONCLUSIONS

These findings suggest that BD is associated with minimal changes in whole blood gene expression independent of medication use but emphasize the importance of accounting for medication use and cell type heterogeneity in psychiatric transcriptomic studies. The results of this study add to mounting evidence of lithium's cell signaling and immune-related mechanisms.

Transcriptomic abnormalities in peripheral blood in bipolar disorder, and discrimination of the major psychoses

We performed a transcriptome-wide meta-analysis and gene co-expression network analysis to identify genes and gene networks dysregulated in the peripheral blood of bipolar disorder (BD) cases relative to unaffected comparison subjects, and determined the specificity of the transcriptomic signatures of BD and schizophrenia (SZ). Nineteen genes and 4 gene modules were significantly differentially expressed in BD cases. Thirteen gene modules were shown to be differentially expressed in a combined case-group of BD and SZ subjects called "major psychosis", including genes biologically linked to apoptosis, reactive oxygen, chromatin remodeling, and immune signaling. No modules were differentially expressed between BD and SZ cases. Machine-learning classifiers trained to separate diagnostic classes based solely on gene expression profiles could distinguish BD cases from unaffected comparison subjects with an area under the curve (AUC) of 0.724, as well as BD cases from SZ cases with AUC = 0.677 in withheld test samples. We introduced a novel and straightforward method called "polytranscript risk scoring" that could distinguish BD cases from unaffected subjects (AUC = 0.672) and SZ cases (AUC = 0.607) significantly better than expected by chance. Taken together, our results highlighted gene expression alterations common to BD and SZ that involve biological processes of inflammation, oxidative stress, apoptosis, and chromatin regulation, and highlight disorder-specific changes in gene expression that discriminate the major psychoses.

Novel genetic susceptibility loci identified by family based whole exome sequencing in Han Chinese schizophrenia patients

Schizophrenia (SCZ) is a highly heritable psychiatric disorder that affects approximately 1% of population around the world. However, early relevant studies did not reach clear conclusions of the genetic mechanisms of SCZ, suggesting that additional susceptibility loci that exert significant influence on SCZ are yet to be revealed. So, in order to identify novel susceptibility genes that account for the genetic risk of SCZ, we performed a systematic family-based study using whole exome sequencing (WES) in 65 Han Chinese families. The analysis of 51 SCZ trios with both unaffected parents identified 22 exonic and 1 splice-site de novo mutations (DNMs) on a total of 23 genes, and showed that 12 genes carried rare protein-altering compound heterozygous mutations in more than one trio. In addition, we identified 26 exonic or splice-site single nucleotide polymorphisms (SNPs) on 18 genes with nominal significance (P < 5 × 10-4) using a transmission disequilibrium test (TDT) in all the families. Moreover, TDT result confirmed a SCZ susceptibility locus on 3p21.1, encompassing the multigenetic region NEK4-ITIH1-ITIH3-ITIH4. Through several different strategies to predict the potential pathogenic genes in silico, we revealed 4 previous discovered susceptibility genes (TSNARE1, PBRM1, STAB1 and OLIG2) and 4 novel susceptibility loci (PSEN1, TLR5, MGAT5B and SSPO) in Han Chinese SCZ patients. In summary, we identified a list of putative candidate genes for SCZ using a family-based WES approach, thus improving our understanding of the pathology of SCZ and providing critical clues to future functional validation.

Williams Syndrome, Human Self-Domestication, and Language Evolution

Language evolution resulted from changes in our biology, behavior, and culture. One source of these changes might be human self-domestication. Williams syndrome (WS) is a clinical condition with a clearly defined genetic basis which results in a distinctive behavioral and cognitive profile, including enhanced sociability. In this paper we show evidence that the WS phenotype can be satisfactorily construed as a hyper-domesticated human phenotype, plausibly resulting from the effect of the WS hemideletion on selected candidates for domestication and neural crest (NC) function. Specifically, we show that genes involved in animal domestication and NC development and function are significantly dysregulated in the blood of subjects with WS. We also discuss the consequences of this link between domestication and WS for our current understanding of language evolution.

Impact of cardiac myosin light chain kinase gene mutation on development of dilated cardiomyopathy

AIMS

Cardiac myosin light chain kinase (cMLCK) phosphorylates ventricular myosin regulatory light chain 2 (MLC2v) and regulates sarcomere and cardiomyocyte organization. However, few data exist regarding the relationship between cMLCK mutations and MLC2v phosphorylation, particularly in terms of developing familial dilated cardiomyopathy (DCM) in whom cMLCK gene mutations were identified. The purpose of the present study was to investigate functional consequences of cMLCK mutations in DCM patients.

METHODS AND RESULTS

The diagnosis of DCM was based on the patients' history and on echocardiography. We screened cMLCK gene mutations in DCM probands with high resolution melting analysis. Known DCM-causing genes mutations were excluded by exome sequencing of family members. MLC2v phosphorylation was analysed by Phos-tag sodium dodecyl sulfate-polyacrylamide gel electrophoresis assays. We also performed ADP-Glo assays for determining the total amount of adenosine triphosphate used in the kinase reaction. Unrelated DCM probands (109 males and 40 females) were enrolled in this study, of which 16 were familial and 133 sporadic. By mutation screening, a truncation variant of c1915-1 g>t (p.Pro639Valfs*15) was identified, which was not detected in 400 chromosomes of 200 healthy volunteers; it is listed in the Human Genetic Variation Database with an allele frequency < 0.001. In the proband, the presence of mutations in known DCM-causing genes was excluded with exome analysis. Familial analysis identified a 19-year-old male carrier who manifested slight left ventricular dilation with preserved systolic function. Phosphorylation assays analysed by Phos-tag SDS-PAGE revealed that the identified p.Pro639Valfs*15 mutation results in a complete lack of kinase activity, although it did not affect wild-type cMLCK activity. ADP-Glo assays confirmed that the mutant cMLCK had no kinase activity, whereas wild-type cMLCK had a Km value of 5.93 ± 1.47 μM and a V_max of 1.28 ± 0.03 mol/min/mol kinase.

CONCLUSIONS

These results demonstrate that a truncation mutation in the cMLCK gene p.Pro639Valfs*15 can be associated with significant impairment of MLC2v phosphorylation and possibly with development of DCM, although a larger study of DCM patients is required to determine the prevalence of this mutation and further strengthen its association with disease development.

Multivariate analysis of genome-wide data to identify potential pleiotropic genes for five major psychiatric disorders using MetaCCA

BACKGROUND

Genome-wide association studies have been extensively applied in identifying SNP associated with major psychiatric disorders. However, the SNPs identified by the prevailing univariate approach only explain a small percentage of the genetic variance of traits, and the extensive data have shown the major psychiatric disorders have common biological mechanisms and the overlapping pathophysiological pathways.

METHODS

We applied the genetic pleiotropy-informed metaCCA method on summary statistics data from the Psychiatric Genomics Consortium Cross-Disorder Group to examine the overlapping genetic relations between the five major psychiatric disorders. Furthermore, to refine all genes, we performed gene-based association analyses for the five disorders respectively using VEGAS2. Gene enrichment analysis was applied to explore the potential functional significance of the identified genes.

RESULTS

After metaCCA analysis, 1147 SNPs reached the Bonferroni corrected threshold (p < 1.06 × 10-6) in the univariate SNP-multivariate phenotype analysis, and 246 genes with a significance threshold (p < 3.85 × 10-6) were identified as potentially pleiotropic genes in the multivariate SNP-multivariate phenotype analysis. By screening the results of gene-based p-values, we identified 37 putative pleiotropic genes which achieved significance threshold in metaCCA analyses and were also associated with at least one disorder in the VEGAS2 analyses.

LIMITATIONS

Alternative approaches and experimental studies may be applied to check whether novel genes could still be identified/substantiated with these methods.

CONCLUSIONS

The metaCCA method identified novel variants associated with psychiatric disorders by effectively incorporating information from different GWAS datasets. Our analyses may provide insights for some common therapeutic approaches of these five major psychiatric disorders based on the pleiotropic genes and common mechanisms identified.

Transcriptome Changes in Relation to Manic Episode

Bipolar disorder (BD) is highly heritable and well known for its recurrent manic and depressive episodes. The present study focused on manic episode in BD patients and aimed to investigate state-specific transcriptome alterations between acute episode and remission, including messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs), and micro-RNAs (miRNAs), using microarray and RNA sequencing (RNA-Seq) platforms. BD patients were enrolled with clinical information, and peripheral blood samples collected at both acute and remission status spanning for at least 2 months were confirmed by follow-ups. Symptom severity was assessed by Young Mania Rating Scale. We enrolled six BD patients as the discovery samples and used the Affymetrix Human Transcriptome Array 2.0 to capture transcriptome data at the two time points. For replication, expression data from Gene Expression Omnibus that consisted of 11 BD patients were downloaded, and we performed a mega-analysis for microarray data of 17 patients. Moreover, we conducted RNA sequencing (RNA-Seq) in additional samples of 7 BD patients. To identify intraindividual differentially expressed genes (DEGs), we analyzed data using a linear model controlling for symptom severity. We found that noncoding genes were of majority among the top DEGs in microarray data. The expression fold change of coding genes among DEGs showed moderate to high correlations (∼0.5) across platforms. A number of lncRNAs and two miRNAs (MIR181B1 and MIR103A1) exhibited high levels of gene expression in the manic state. For coding genes, we reported that the taste function-related genes, including TAS2R5 and TAS2R3, may be mania state-specific markers. Additionally, four genes showed a nominal p-value of less than 0.05 in all our microarray data, mega-analysis, and RNA-Seq analysis. They were upregulated in the manic state and consisted of MS4A14, PYHIN1, UTRN, and DMXL2, and their gene expression patterns were further validated by quantitative real-time polymerase chain reaction (PCR) (qRT-PCR). We also performed weight gene coexpression network analysis to identify gene modules for manic episode. Genes in the mania-related modules were different from the susceptible loci of BD obtained from genome-wide association studies, and biological pathways in relation to these modules were mainly related to immune function, especially cytokine-cytokine receptor interaction. Results of the present study elucidated potential molecular targets and genomic networks that are involved in manic episode. Future studies are needed to further validate these biomarkers for their roles in the etiology of bipolar illness.

Alzheimer's disease DNA methylome of pyramidal layers in frontal cortex: laser-assisted microdissection study

OBJECTIVE

To study DNA methylation patterns of cortical pyramidal layers susceptible to late-onset Alzheimer's disease (LOAD) neurodegeneration.

METHODS

Laser-assisted microdissection to select pyramidal layers' cells in frontal cortex of 32 human brains (18 LOAD) and Infinium DNA Methylation 450K analysis were performed to find differential methylated positions and regions, in addition to the corresponding gene set functional enrichment analyses.

RESULTS

Differential hypermethylation in several genomic regions and genes mainly in HOXA3, GSTP1, CXXC1-3 and BIN1. The functional enrichment analysis revealed genes significantly related to oxidative-stress and synapsis.

CONCLUSION

The present results indicate the differentially methylated genes related to neural projections, synapsis, oxidative stress and epigenetic regulator genes and represent the first epigenome of cortical pyramidal layers in LOAD.

Convergent analysis of genome-wide genotyping and transcriptomic data suggests association of zinc finger genes with lithium response in bipolar disorder

Lithium is the mainstay treatment in bipolar disorder (BD) for its effectiveness in the acute phases of illness and in prevention of recurrences. Lithium's mechanism of action is complex, and while it modulates the function of hundreds of molecular targets, most of these effects could be unspecific and not relevant for its clinical efficacy. In this study, we applied an integrated analytical approach using genome-wide expression and genotyping data from BD patients to identify lithium-responsive genes that may serve as biomarkers of its efficacy. To this purpose, we tested the effect of treatment with lithium chloride 1 mM on the transcriptome of lymphoblasts from 10 lithium responders (LR) and 10 nonresponders (NR) patients and identified genes significantly influenced by the treatment exclusively in LR. These findings were integrated with gene-based analysis on genome-wide genotyping data from an extended sample of 205 BD patients characterized for lithium response. The expression of 29 genes was significantly changed by lithium exclusively in LR. Gene-based analysis showed that two of these genes, zinc finger protein 429 (ZNF429) and zinc finger protein 493 (ZNF493), were also significantly associated with lithium response. Validation with quantitative real-time polymerase chain reaction confirmed the lithium-induced downregulation of ZNF493 in LR (p = .036). Using convergent analyses of genome-wide expression and genotyping data, we identified ZNF493 as a potential lithium-responsive target that may be involved in modulating lithium efficacy in BD. To our knowledge, this is the first evidence supporting the involvement of zinc finger proteins in lithium response.

Inter-α-inhibitor deficiency in the mouse is associated with alterations in anxiety-like behavior, exploration and social approach

In recent years, several genome-wide association studies have identified candidate regions for genetic susceptibility in major mood disorders. Most notable are regions in a locus in chromosome 3p21, encompassing the genes NEK4-ITIH1-ITIH3-ITIH4. Three of these genes represent heavy chains of the composite protein inter-α-inhibitor (IαI). In order to further establish associations of these genes with mood disorders, we evaluated behavioral phenotypes in mice deficient in either Ambp/bikunin, which is necessary for functional ITIH1 and ITIH3 complexes, or in Itih4, the gene encoding the heavy chain Itih4. We found that loss of Itih4 had no effect on the behaviors tested, but loss of Ambp/bikunin led to increased anxiety-like behavior in the light/dark and open field tests and reduced exploratory activity in the elevated plus maze, light/dark preference and open field tests. Ambp/bikunin knockout mice also exhibited a sex-dependent exaggeration of acoustic startle responses, alterations in social approach during a three-chamber choice test, and an elevated fear conditioning response. These results provide experimental support for the role of ITIH1/ITIH3 in the development of mood disorders.

Comparison of salivary testosterone levels in different phases of bipolar I disorder and control group

Background:

Testosterone is considered as a primary sex hormone, also known as an important anabolic steroid, that may involve in various mental disorders such as bipolar I disorder (BID). The goal of this study was to compare the testosterone salivary levels between different phases of BID and its association with the clinical features of BID.

Materials and Methods:

In a case–control study, 15 patients in the mania phase, 10 patients in the depression phase, and 16 in the euthymia phase were selected as patient groups. 18 healthy sex- and age-matched individuals were considered as healthy control group. Salivary samples obtained from all patients and control group and levels of testosterone were determined in saliva using an enzyme-linked immunosorbent assay. All statistical calculations were conducted with the software Statistical Package for Social Science version 20 (IBM Inc., Chicago, IL, USA).

Results:

The mean testosterone level in euthymia phase was 186.34 ± 182.62 pg/mL, mania phase was 239.29 ± 273.22 pg/mL, depression was 153.49 ± 222.50 pg/mL, and healthy participants was 155.73 ± 126.0 pg/mL; no significant difference was found between groups (P = 0.68.(No statistically significant differences were found between psychotic and nonpsychotic as well as between patients who attempted suicide and nonattempter patients in terms of testosterone levels (P > 0.1).

Conclusion:

Our findings do not reveal significant difference between different phases of BID in terms of salivary testosterone levels. However, more comprehensive studies with larger sample size are required to confirm our findings.

Activated immune-inflammatory pathways are associated with long-standing depressive symptoms: Evidence from gene-set enrichment analyses in the Young Finns Study

We used genome wide expression (GWE) data of circulating blood cells and pathway analysis to investigate the inflammatory and other molecular pathways that may be associated with long-standing depressive symptoms. Participants were 607 women and 316 men (mean age 42 years) from the Young Finns Study who participated in three consecutive study phases in 2001, 2007 and 2012. Using Gene-set enrichment analyses (GSEA) we focused our analyses to pathways (available in MSigDB database) that are likely to affect immunological and inflammatory processes. GSEA were performed for blood cell GWE data in 2012. Depressive symptoms were assessed using a modified 21-item Beck Depression Inventory in each of the three study phases. Participants who scored in the top quartile of depressive symptoms in each of the three measurement points (n = 191) differed from other participants (n = 732) in several gene-set pathways related to inflammatory processes or immune-inflammatory signaling including interleukin (IL-1) pathway, and pathways related to various immuno-inflammatory processes, such as toll-like, the NEF protein, the nuclear factor kB, the kinase AKT and the mature B cell antigen receptor pathway (false discovery rates, FDRs<0.12). The results provide novel genome wide molecular evidence that support the association between chronic depressive symptoms and altered immune-inflammatory regulation.

A composite peripheral blood gene expression measure as a potential diagnostic biomarker in bipolar disorder

Gene expression in peripheral blood has the potential to inform on pathophysiological mechanisms and has emerged as a viable avenue for the identification of biomarkers. Here, we aimed to identify gene expression candidate genes and to explore the potential for a composite gene expression measure as a diagnostic and state biomarker in bipolar disorder. First, messenger RNA levels of 19 candidate genes were assessed in peripheral blood mononuclear cells of 37 rapid cycling bipolar disorder patients in different affective states (depression, mania and euthymia) during a 6-12-month period and in 40 age- and gender-matched healthy control subjects. Second, a composite gene expression measure was constructed in the first half study sample and independently validated in the second half of the sample. We found downregulation of POLG and OGG1 expression in bipolar disorder patients compared with healthy control subjects. In patients with bipolar disorder, upregulation of NDUFV2 was observed in a depressed state compared with a euthymic state. The composite gene expression measure for discrimination between patients and healthy control subjects on the basis of 19 genes generated an area under the receiver-operating characteristic curve of 0.81 (P < 0.0001) in sample 1, which was replicated with a value of 0.73 (P < 0.0001) in sample 2, corresponding with a moderately accurate test. The present findings of altered POLG, OGG1 and NDUFV2 expression point to disturbances within mitochondrial function and DNA repair mechanisms in bipolar disorder. Further, a composite gene expression measure could hold promise as a potential diagnostic biomarker.