Prediction of susceptibility to major depression by a model of interactions of multiple functional genetic variants and environmental factors

The interaction network of the proteasome assembly chaperone PSMD9 regulates proteostasis

Functional networks in cells are created by physical, genetic, and regulatory interactions. Mapping them and annotating their functions by available methods remains a challenge. We use affinity purification mass spectrometry (AP-MS) coupled with SLiMFinder to discern such a network involving 26S proteasome non-ATPase regulatory subunit 9 (PSMD9), a chaperone of proteasome assembly. Approximately 20% of proteins within the PSMD9 interactome carry a short linear motif (SLiM) of the type 'EXKK'. The binding of purified PSMD9 with the peptide sequence ERKK, proteins heterogeneous nuclear ribonucleoproteins A2/B1 (hnRNPA2B1; containing ERKK), and peroxiredoxin-6 (PRDX6; containing EAKK) provided proof of principle for this motif-driven network. The EXKK motif in the peptide primarily interacts with the coiled-coil N domain of PSMD9, a unique interaction not reported for any coiled-coil domain. PSMD9 knockout (KO) HEK293 cells experience endoplasmic reticulum (ER) stress and respond by increasing the unfolded protein response (UPR) and reducing the formation of aggresomes and lipid droplets. Trans-expression of PSMD9 in the KO cells rescues lipid droplet formation. Overexpression of PSMD9 in HEK293 cells results in reduced UPR, and increased lipid droplet and aggresome formation. The outcome argues for the prominent role of PSMD9 in maintaining proteostasis. Probable mechanisms involve the binding of PSMD9 to binding immunoglobulin protein (BIP/GRP78; containing EDKK), an endoplasmic reticulum chaperone and key regulator of the UPR, and fatty acid synthase (FASN; containing ELKK), involved in fatty acid synthesis/lipid biogenesis. We propose that PSMD9 acts as a buffer in the cellular milieu by moderating the UPR and enhancing aggresome formation to reduce stress-induced proteotoxicity. Akin to waves created in ponds that perpetuate to a distance, perturbing the levels of PSMD9 would cause ripples down the networks, affecting final reactions in the pathway, one of which is altered proteostasis.

Krill oil treatment ameliorates lipid metabolism imbalance in chronic unpredicted mild stress-induced depression-like behavior in mice

The pathology of depression involves various factors including the interaction between genes and the environment. The deficiency of n-3 polyunsaturated fatty acids (n-3 PUFAs) in the brain and depressive symptoms are closely related. Krill oil contains abundant amounts of n-3 PUFAs incorporated in phosphatidylcholine. However, the effect of krill oil treatment on depression-like behaviors induced by chronic stress and its molecular mechanism in the brain remain poorly understood. Here, we used a chronic unpredictable mild stress (CUMS) model to evaluate the effect of krill oil on depression-like behaviors and explored its molecular mechanism through lipid metabolomics and mRNA profiles in the whole brain. We observed that CUMS-induced depression-like behaviors were ameliorated by krill oil supplementation in mice. The metabolism of glycerophospholipids and sphingolipids was disrupted by CUMS treatment, which were ameliorated after krill oil supplementation. Further analysis found that differently expressed genes after krill oil supplementation were mainly enriched in the membrane structures and neuroactive ligand-receptor interaction pathway, which may be responsible for the amelioration of CUMS-induced depression-like behaviors. Altogether, our results uncovered the relationship between lipid metabolism and CUMS, and provided new strategies for the prevention and treatment of depression.

Establishing 20S Proteasome Genetic, Translational and Post-Translational Status from Precious Biological and Patient Samples with Top-Down MS

The mammalian 20S catalytic core of the proteasome is made of 14 different subunits (α1-7 and β1-7) but exists as different subtypes depending on the cell type. In immune cells, for instance, constitutive catalytic proteasome subunits can be replaced by the so-called immuno-catalytic subunits, giving rise to the immunoproteasome. Proteasome activity is also altered by post-translational modifications (PTMs) and by genetic variants. Immunochemical methods are commonly used to investigate these PTMs whereby protein-tagging is necessary to monitor their effect on 20S assembly. Here, we present a new miniaturized workflow combining top-down and bottom-up mass spectrometry of immunopurified 20S proteasomes that analyze the proteasome assembly status as well as the full proteoform footprint, revealing PTMs, mutations, single nucleotide polymorphisms (SNPs) and induction of immune-subunits in different biological samples, including organoids, biopsies and B-lymphoblastoid cell lines derived from patients with proteasome-associated autoinflammatory syndromes (PRAAS). We emphasize the benefits of using top-down mass spectrometry in preserving the endogenous conformation of protein modifications, while enabling a rapid turnaround (1 h run) and ensuring high sensitivity (1–2 pmol) and demonstrate its capacity to semi-quantify constitutive and immune proteasome subunits.

A GHRHR founder mutation causes isolated growth hormone deficiency type IV in a consanguineous Pakistani family

Background

Isolated growth hormone deficiency (IGHD) is caused by a severe shortage or absence of growth hormone (GH), which results in aberrant growth and development. Patients with IGHD type IV (IGHD4) have a short stature, reduced serum GH levels, and delayed bone age.

Objectives

To identify the causative mutation of IGHD in a consanguineous family comprising four affected patients with IGHD4 (MIM#618157) and explore its functional impact in silico.

Methods

Clinical and radiological studies were performed to determine the phenotypic spectrum and hormonal profile of the disease, while whole-exome sequencing (WES) and Sanger sequencing were performed to identify the disease-causing mutation. In-silico studies involved protein structural modeling and docking, and molecular dynamic simulation analyses using computational tools. Finally, data from the Qatar Genome Program (QGP) were screened for the presence of the founder variant in the Qatari population.

Results

All affected individuals presented with a short stature without gross skeletal anomalies and significantly reduced serum GH levels. Genetic mapping revealed a homozygous nonsense mutation [NM_000823:c.G214T:p.(Glu72*)] in the third exon of the growth-hormone-releasing hormone receptor gene GHRHR (MIM#139191) that was segregated in all patients. The substituted amber codon (UAG) seems to truncate the protein by deleting the C-terminus GPCR domain, thus markedly disturbing the GHRHR receptor and its interaction with the growth hormone-releasing hormone.

Conclusion

These data support that a p.Glu72* founder mutation in GHRHR perturbs growth hormone signaling and causes IGHD type IV. In-silico and biochemical analyses support the pathogenic effect of this nonsense mutation, while our comprehensive phenotype and hormonal profiling has established the genotype-phenotype correlation. Based on the current study, early detection of GHRHR may help in better therapeutic intervention.

The impact of HTR1A and HTR1B methylation combined with stress/genotype on early antidepressant efficacy

AIMS

Antidepressants are effective in the treatment of major depressive disorder (MDD), while many patients fail to respond to antidepressants. Both 5-HT1A (HTR1A) and 5-HT1B (HTR1B) receptors play an important role in antidepressant activity. Meanwhile, DNA methylation is associated with MDD and antidepressant efficacy. In this study we investigate the influence of HTR1A and HTR1B methylation combined with stress/genotype on antidepressant efficacy.

METHODS

A total of 291 MDD patients and 100 healthy controls received the Life Events Scale (LES) and the Childhood Trauma Questionnaire (CTQ) as stress assessment. Eight single nucleotide polymorphisms (SNPs) of HTR1A and HTR1B involved in antidepressant mechanisms were tested. Methylation status in 181 cytosine-phosphate-guanine (CpG) sites of HTR1A and HTR1B were assessed. All MDD patients were divided into response (RES) and non-response (NRES) after 2 weeks of antidepressant treatment. Logistic regression was conducted for interactions between methylation, NLES/CTQ score and genotype.

RESULTS

Low HTR1A-2-143 methylation is connected with better antidepressant efficacy in subgroup. Low HTR1A-2-143 methylation combined with low CTQ score is related to better antidepressant efficacy. The interaction between high HTR1B methylation with the rs6298 AA/AG genotype affects better antidepressant efficacy.

CONCLUSIONS

HTR1A and HTR1B methylation combined with stress/genotype is associated with antidepressant efficacy.

Genetic contributions to alcohol use disorder treatment outcomes: a genome-wide pharmacogenomics study

Naltrexone can aid in reducing alcohol consumption, while acamprosate supports abstinence; however, not all patients with alcohol use disorder (AUD) benefit from these treatments. Here we present the first genome-wide association study of AUD treatment outcomes based on data from the COMBINE and PREDICT studies of acamprosate and naltrexone, and the Mayo Clinic CITA study of acamprosate. Primary analyses focused on treatment outcomes regardless of pharmacological intervention and were followed by drug-stratified analyses to identify treatment-specific pharmacogenomic predictors of acamprosate and naltrexone response. Treatment outcomes were defined as: (1) time until relapse to any drinking (TR) and (2) time until relapse to heavy drinking (THR; ≥ 5 drinks for men, ≥4 drinks for women in a day), during the first 3 months of treatment. Analyses were performed within each dataset, followed by meta-analysis across the studies (N = 1083 European ancestry participants). Single nucleotide polymorphisms (SNPs) in the BRE gene were associated with THR (min p = 1.6E-8) in the entire sample, while two intergenic SNPs were associated with medication-specific outcomes (naltrexone THR: rs12749274, p = 3.9E-8; acamprosate TR: rs77583603, p = 3.1E-9). The top association signal for TR (p = 7.7E-8) and second strongest signal in the THR (p = 6.1E-8) analysis of naltrexone-treated patients maps to PTPRD, a gene previously implicated in addiction phenotypes in human and animal studies. Leave-one-out polygenic risk score analyses showed significant associations with TR (p = 3.7E-4) and THR (p = 2.6E-4). This study provides the first evidence of a polygenic effect on AUD treatment response, and identifies genetic variants associated with potentially medication-specific effects on AUD treatment response.

Climate change and mental health: a commentary

Climate change represents a major global challenge. Some hallmarks of climate change that have been connected to human activity include an increase of 0.8-1.2 °C in global temperatures as well as the warming of upper ocean water. Importantly, approximately 500 million people worldwide face the consequences of desertification. Simultaneously, the world population has grown from 1.6 billion in 1900 to 7.7 billion today, greatly exacerbating the human toll of devastating environmental disasters, which result in increasingly larger and more common mass migrations that also fuel human trafficking and modern-day slavery. The mental health outcomes are staggering and include, in the context of chronic stress, addiction, anxiety disorders, post-traumatic stress disorder (PTSD), bipolar disorder, major depression, and suicidality. Mental health practitioners, healthcare systems, and governments across the world need to be prepared to address the mental health sequelae of climate change.

Impulsive and Omission Errors: Potential Temporal Processing Endophenotypes in ADHD

Temporal processing (TP) is associated with functions such as perception, verbal skills, temporal perspective, and future planning, and is intercorrelated with working memory, attention, and inhibitory control, which are highly impaired in individuals with attention deficit hyperactivity disorder (ADHD). Here we evaluate TP measures as potential endophenotypes in Caribbean families ascertained from probands affected by ADHD. A total of 232 individuals were recruited and clinically evaluated using an extensive battery of neuropsychological tasks and reaction time (RT)-based task paradigms. Further, the heritability (genetic variance underpinning phenotype) was estimated as a measure of the genetics apportionment. A predictive framework for ADHD diagnosis was derived using these tasks. We found that individuals with ADHD differed from controls in neuropsychological tasks assessing mental control, visual-verbal memory, verbal fluency, verbal, and semantic fluency. In addition, TP measures such as RT, errors, and variability were also affected in individuals with ADHD. Moreover, we determined that only omission and commission errors had significant heritability. In conclusion, we have disentangled omission and commission errors as possible TP endophenotypes in ADHD, which can be suitable to assess the neurobiological and genetic basis of ADHD. A predictive model using these endophenotypes led to remarkable sensitivity, specificity, precision and classification rate for ADHD diagnosis, and may be a useful tool for patients' diagnosis, follow-up, and longitudinal assessment in the clinical setting.

Ciliary GPCR-based transcriptome as a key regulator of cilia length control

The primary cilium is a plasma membrane-protruding sensory organelle that efficiently conveys signaling cascades in a highly ordered microenvironment. Its signaling is mediated, in part, by a limited set of GPCRs preferentially enriched in the cilium membrane. This includes melanin-concentrating hormone (MCH) receptor 1 (MCHR1), which plays a role in feeding and mood. In addition to its receptor composition, the length of the cilium is a characteristic parameter that is implicated in its function. We previously found that MCH can dynamically shorten cilia length via the Gi/o and Akt pathways in both MCHR1-expressing hTERT-RPE1 cells (hRPE1 cells) and rat hippocampal neurons. However, the detailed mechanisms by which MCH regulates cilia length through ciliary MCHR1 remains unclear. In this study, we aimed to determine the transcriptome changes in MCHR1-expressing hRPE1 cells in response to MCH to identify the target molecules involved in cilia length regulation via MCHR1 activation. RNA sequencing analysis of ciliated cells subjected to MCH treatment showed upregulation of 424 genes and downregulation of 112 genes compared with static control cells. Validation by quantitative real-time PCR, knocking down, and CRISPR/Cas9-mediated knockout technology identified a molecule, PDZ and LIM domain-containing protein 5 (PDLIM5). Thus, it was considered as the most significant key factor for MCHR1-mediated shortening of cilia length. Additional analyses revealed that the actin-binding protein alpha-actinin 1/4 is a crucial downstream target of the PDLIM5 signaling pathway that exerts an effect on MCHR1-induced cilia shortening. In the endogenous MCHR1-expressing hippocampus, transcriptional upregulation of PDLIM5 and actinin 1/4, following the application of MCH, was detected when the MCHR1-positive cilia were shortened. Together, our transcriptome study based on ciliary MCHR1 function uncovered a novel and important regulatory step underlying cilia length control. These results will potentially serve as a basis for understanding the mechanism underlying the development of obesity and mood disorders.

Analysis of Major Depression Risk Genes Reveals Evolutionary Conservation, Shared Phenotypes, and Extensive Genetic Interactions

Major depressive disorder (MDD) affects around 15% of the population at some stage in their lifetime. It can be gravely disabling and it is associated with increased risk of suicide. Genetics play an important role; however, there are additional environmental contributions to the pathogenesis. A number of possible risk genes that increase liability for developing symptoms of MDD have been identified in genome-wide association studies (GWAS). The goal of this study was to characterize the MDD risk genes with respect to the degree of evolutionary conservation in simpler model organisms such as Caenorhabditis elegans and zebrafish, the phenotypes associated with variation in these genes and the extent of network connectivity. The MDD risk genes showed higher conservation in C. elegans and zebrafish than genome-to-genome comparisons. In addition, there were recurring themes among the phenotypes associated with variation of these risk genes in C. elegans. The phenotype analysis revealed enrichment for essential genes with pleiotropic effects. Moreover, the MDD risk genes participated in more interactions with each other than did randomly-selected genes from similar-sized gene sets. Syntenic blocks of risk genes with common functional activities were also identified. By characterizing evolutionarily-conserved counterparts to the MDD risk genes, we have gained new insights into pathogenetic processes relevant to the emergence of depressive symptoms in man.

PDE6C: Novel Mutations, Atypical Phenotype, and Differences Among Children and Adults

Purpose

Genetic variation in PDE6C is associated with achromatopsia and cone dystrophy, with only a few reports of cone-rod dystrophy in the literature. We describe two pediatric and two adult patients with PDE6C related cone and cone-rod dystrophy and the first longitudinal data of a pediatric patient with PDE6C-related cone dystrophy.

Methods

This cohort of four patients underwent comprehensive ophthalmologic evaluation at the National Eye Institute's Ophthalmic Genetics clinic, including visual field testing, retinal imaging and electroretinogram (ERG). Next-generation sequencing-based genetic testing was performed and subsequent analysis of the variants was done through three-dimensional protein models generated by Phyre2 and Chimera.

Results

All cases shared decreased best-corrected visual acuity and poor color discrimination. Three of the four patients had a cone-rod dystrophy, presenting with an ERG showing decreased amplitude on both photopic and scotopic waveforms and a mild to moderately constricted visual field. One of the children was diagnosed with cone dystrophy, having a preserved peripheral field. The children had none to minor structural retinal changes, whereas the adults had clear macular dystrophy.

Conclusions

PDE6C-related cone-rod dystrophy consists of a severe phenotype characterized by early-onset nystagmus, decreased best-corrected visual acuity, poor color discrimination, progressive constriction of the visual field, and night blindness. Our work contributes with valuable information toward understanding the visual prognosis and allelic heterogeneity of PDE6C-related cone and cone-rod dystrophy.

Rare Recurrent Variants in Noncoding Regions Impact Attention-Deficit Hyperactivity Disorder (ADHD) Gene Networks in Children of both African American and European American Ancestry

Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder with poorly understood molecular mechanisms that results in significant impairment in children. In this study, we sought to assess the role of rare recurrent variants in non-European populations and outside of coding regions. We generated whole genome sequence (WGS) data on 875 individuals, including 205 ADHD cases and 670 non-ADHD controls. The cases included 116 African Americans (AA) and 89 European Americans (EA), and the controls included 408 AA and 262 EA. Multiple novel rare recurrent variants were identified in exonic regions, functionally classified as stop-gains and frameshifts for known ADHD genes. Deletion in introns of the protocadherins families and the ncRNA HGB8P were identified in two independent EA ADHD patients. A meta-analysis of the two ethnicities for differential ADHD recurrent variants compared to controls shows a small number of overlaps. These results suggest that rare recurrent variants in noncoding regions may be involved in the pathogenesis of ADHD in children of both AA and EA ancestry; thus, WGS could be a powerful discovery tool for studying the molecular mechanisms of ADHD.

Rare Functional Variants Associated with Antidepressant Remission in Mexican-Americans: Short title: Antidepressant remission and pharmacogenetics in Mexican-Americans

INTRODUCTION

Rare genetic functional variants can contribute to 30-40% of functional variability in genes relevant to drug action. Therefore, we investigated the role of rare functional variants in antidepressant response.

METHOD

Mexican-American individuals meeting the Diagnostic and Statistical Manual-IV criteria for major depressive disorder (MDD) participated in a prospective randomized, double-blind study with desipramine or fluoxetine. The rare variant analysis was performed using whole-exome genotyping data. Network and pathway analyses were carried out with the list of significant genes.

RESULTS

The Kernel-Based Adaptive Cluster method identified functional rare variants in 35 genes significantly associated with treatment remission (False discovery rate, FDR <0.01). Pathway analysis of these genes supports the involvement of the following gene ontology processes: olfactory/sensory transduction, regulation of response to cytokine stimulus, and meiotic cell cycleprocess.

LIMITATIONS

Our study did not have a placebo arm. We were not able to use antidepressant blood level as a covariate. Our study is based on a small sample size of only 65 Mexican-American individuals. Further studies using larger cohorts are warranted.

CONCLUSION

Our data identified several rare functional variants in antidepressant drug response in MDD patients. These have the potential to serve as genetic markers for predicting drug response.

TRIAL REGISTRATION

ClinicalTrials.gov NCT00265291.

AVPR1A main effect and OXTR-by-environment interplay in individual differences in depression level

Background

Multiple studies of depression indicated a significant role of gene-by-environment interactions; however, they are mainly limited to the examination of modulating effect of recent stressful life events. Other environmental factors occurring at different stages of ante- and postnatal development may affect the association between multiple genes and depression. The study aimed to analyze the main and haplotype-based effect of serotonergic system and HPA-axis gene polymorphisms on depression and to detect gene-by-environment interaction models explaining individual variance in depression in mentally healthy young adults from Russia.

Methods

Depression score was assessed using Beck Depression Inventory (BDI) in 623 healthy individuals (81% women; 17-25 years) of Caucasian origin (Russians, Tatars, Udmurts) from Russia. The main- and gene-based effects of 12 SNPs in SLC6A4 (5-HTTLPR, rs1042173), HTR2A (rs7322347), OXTR (rs7632287, rs2254298, rs13316193, rs53576, rs2228485, rs237911), AVPR1A (rs3803107, rs1042615), and AVPR1B (rs33911258) genes, and gene-by-environment interactions were tested with linear regression models (PLINK v.1.9) adjusted for multiple comparisons.

Results

We observed ethnicity-specific main effect of the AVPR1A rs3803107 (P = 0.003; P_FDR = 0.047) and gene-based effect of the OXTR gene (Р = 0.005; P_perm = 0.034) on BDI-measured depression, and modifying effect of paternal care on OXTR rs53576 (P = 0.004; P_FDR = 0.012) and birth order on OXTR rs237911 (P = 0.006; P_FDR = 0.018) association with depression level.

Limitations

A hypothesis driven candidate gene approach, which examined a limited number of genetic variants in a moderately large sample, was used.

Conclusions

Our preliminary findings indicate that familial environment may play a permissive role modulating the manifestation of OXTR-based depression variance in mentally healthy subjects.

PDLIM5 improves depression-like behavior of prenatal stress offspring rats via methylation in male, but not female

OBJECTIVE

Prenatal stress (PS) contributes to depression-like behavior in the offspring. PDLIM5 is involved in the onset of mental disorders. This study is to investigate the role and mechanism of PDLIM5 in depression-like behavior of PS offspring rats.

METHODS

PS model was used to analyze the effects of different treatments to PS offspring rats with different sex, including PDLIM5, PDLIM5 shRNA and 5-aza-2' -deoxycytidine (5-azaD). The depression-like behavior was assessed by the sucrose preference test (SPT) and forced swimming test (FST). The mRNA and protein expression levels of PDLIM5 in the hippocampus of PS offspring rats were detected by qRT-PCR and western blot, respectively. The methylation of PDLIM5 promoter were analyzed by bisulfite sequencing.

RESULTS

Our data revealed that PS offspring rats showed a significant decrease in sucrose preference and a prolonged immobility time. Injection of PDLIM5 significantly improved the depression-like behavior in PS offspring rats, whereas administration of PDLIM5 shRNA aggravated it. In addition, PDLIM5 expression was decreased at the mRNA and protein levels, and the methylation level of PDLIM5 promoter was increased in hippocampus of PS male but not female offspring rats. Furthermore, microinjection of 5-azaD improved the PS induced depression-like behavior in offspring rats. Moreover, in male PS offspring rats, microinjection of 5-azaD reversed the effect of PS on PDLIM5 expression and promoter methylation.

CONCLUSION

PDLIM5 can significantly improve the depression-like behavior of both male and female PS offspring rats, while the PDLIM5 promoter methylation is only observed in male PS offspring rats. Our study may provide new mechanism for the pathogenesis of depression and experimental evidence for sex-based precise treatment.

Susceptibility to cellular stress in PS1 mutant N2a cells is associated with mitochondrial defects and altered calcium homeostasis

Presenilin 1 (PS1) mutations are the most common cause of familial Alzheimer's disease (FAD). PS1 also plays a role in cellular processes such as calcium homeostasis and autophagy. We hypothesized that mutant presenilins increase cellular vulnerability to stress. We stably expressed human PS1, mutant PS1E280A and mutant PS1Δ9 in mouse neuroblastoma N2a cells. We examined early signs of stress in different conditions: endoplasmic reticulum (ER) stress, calcium overload, oxidative stress, and Aβ 1-42 oligomers toxicity. Additionally, we induced autophagy via serum starvation. PS1 mutations did not have an effect in ER stress but PS1E280A mutation affected autophagy. PS1 overexpression influenced calcium homeostasis and generated mitochondrial calcium overload modifying mitochondrial function. However, the opening of the mitochondrial permeability transition pore (MPTP) was affected in PS1 mutants, being accelerated in PS1E280A and inhibited in PS1Δ9 cells. Altered autophagy in PS1E280A cells was neither modified by inhibition of γ-secretase, nor by ER calcium retention. MPTP opening was directly regulated by γ-secretase inhibitors independent on organelle calcium modulation, suggesting a novel direct role for PS1 and γ-secretase in mitochondrial stress. We identified intrinsic cellular vulnerability to stress in PS1 mutants associated simultaneously with both, autophagic and mitochondrial function, independent of Aβ pathology.

NG2-glia cell proliferation and differentiation by glial growth factor 2 (GGF2), a strategy to promote functional recovery after ischemic stroke

Stroke is the leading cause of adult disability. Spontaneous functional recovery occurs after ischemic stroke, but it is very limited. Therefore, it is urgent to find a strategy to promote functional recovery after stroke in clinical setting. Gray matter damage has received extensive attention owing to the important roles of the gray matter in synaptic plasticity, cognitive, and motor function. However, stroke also causes white matter damage, which accounts for half of the infarct volume and can be aggravated by blood brain barrier damage. Disruption of white matter integrity, which is characterized by death of oligodendrocytes (OLs), loss of myelin, and axonal injury, greatly contributes to impaired neurological function. Impaired proliferation and differentiation of OL precursor cell (OPC, NG2-glia cells) play an important role in limited functional recovery after ischemic stroke and inhibitor of differentiation 2 (ID2) is a key factor controlling NG2-glia cells differentiation. It has been reported that the number of NG2-glia cells in the peri-infarction area significantly increases after ischemic stroke and glial growth factor (GGF2) administration promotes the proliferation and differentiation of NG2-glia cells as well as functional recovery after spinal cord injury. On the basis of the important roles of GGF2 in functional recovery and those of ID2 in NG2-glia cell proliferation and differentiation, we propose that after binding with the ErBb receptor on the surface of NG2-glia cells, GGF2 promotes NG2-glia cell proliferation and differentiation, thereby repairing BBB and white matter integrity and promoting neural functional recovery after ischemic stroke.

Co-shared genetics and possible risk gene pathway partially explain the comorbidity of schizophrenia, major depressive disorder, type 2 diabetes, and metabolic syndrome

Schizophrenia (SCZ) and major depressive disorder (MDD) in treatment-naive patients are associated with increased risk for type 2 diabetes (T2D) and metabolic syndrome (MetS). SCZ, MDD, T2D, and MetS are often comorbid and their comorbidity increases cardiovascular risk: Some risk genes are likely co-shared by them. For instance, transcription factor 7-like 2 (TCF7L2) and proteasome 26S subunit, non-ATPase 9 (PSMD9) are two genes independently reported as contributing to T2D and SCZ, and PSMD9 to MDD as well. However, there are scarce data on the shared genetic risk among SCZ, MDD, T2D, and/or MetS. Here, we briefly describe T2D, MetS, SCZ, and MDD and their genetic architecture. Next, we report separately about the comorbidity of SCZ and MDD with T2D and MetS, and their respective genetic overlap. We propose a novel hypothesis that genes of the prolactin (PRL)-pathway may be implicated in the comorbidity of these disorders. The inherited predisposition of patients with SCZ and MDD to psychoneuroendocrine dysfunction may confer increased risk of T2D and MetS. We illustrate a strategy to identify risk variants in each disorder and in their comorbid psychoneuroendocrine and mental-metabolic dysfunctions, advocating for studies of genetically homogeneous and phenotype-rich families. The results will guide future studies of the shared predisposition and molecular genetics of new homogeneous endophenotypes of SCZ, MDD, and metabolic impairment.

[Postpartum depression: association with genetic polymorphisms of noradrenaline metabolic enzymes and the risk factors]

OBJECTIVE

To investigate the association of genetic polymorphisms of norepinephrine metabolizing enzymes with postpartum depression and analyze the risk factors for postpartum depression in women following cesarean section.

METHODS

A total of 591 Chinese woman of Han Nationality undergoing caesarean section were enrolled in this study. The diagnosis of postpartum depression was established for an Edinburgh Postnatal Depression Scale (EPDS) score ≥9. For all the women without antepartum depression, the genotypes of catechol-O-methyltransferase (COMT; at 5 sites including rs2020917 and rs737865) and monoamine oxidase A (rs6323) were determined using Sequenom^? Mass Array single nucleotide polymorphism (SNP) analysis. We analyzed the contribution of the genetic factors (SNPs, linkage disequilibrium and haplotype) to postpartum depression and performed logistic regression analysis to identify all the potential risk factors for postpartum depression and define the interactions between the genetic and environmental factors.

RESULTS

The incidence of postpartum depression was 18.1% in this cohort. Univariate analysis suggested that COMT polymorphism at rs2020917 (TT genotype) and rs737865 (GG genotype) were significantly correlated with the occurrence of postpartum depression (P &lt; 0.05). Logistic regression analysis showed that COMT polymorphism at rs2020917 (TT genotype) and rs737865 (GG genotype), severe stress during pregnancy, and domestic violence were the risk factors for postpartum depression (P &lt; 0.05); no obvious interaction was found between the genetic polymorphisms and the environmental factors in the occurrence of postpartum depression.

CONCLUSIONS

The rs2020917TT and rs737865GG genotypes of COMT, stress in pregnancy, and domestic violence are the risk factors for postpartum depression.

ADGRL3 (LPHN3) variants predict substance use disorder

Genetic factors are strongly implicated in the susceptibility to develop externalizing syndromes such as attention-deficit/hyperactivity disorder (ADHD), oppositional defiant disorder, conduct disorder, and substance use disorder (SUD). Variants in the ADGRL3 (LPHN3) gene predispose to ADHD and predict ADHD severity, disruptive behaviors comorbidity, long-term outcome, and response to treatment. In this study, we investigated whether variants within ADGRL3 are associated with SUD, a disorder that is frequently co-morbid with ADHD. Using family-based, case-control, and longitudinal samples from disparate regions of the world (n = 2698), recruited either for clinical, genetic epidemiological or pharmacogenomic studies of ADHD, we assembled recursive-partitioning frameworks (classification tree analyses) with clinical, demographic, and ADGRL3 genetic information to predict SUD susceptibility. Our results indicate that SUD can be efficiently and robustly predicted in ADHD participants. The genetic models used remained highly efficient in predicting SUD in a large sample of individuals with severe SUD from a psychiatric institution that were not ascertained on the basis of ADHD diagnosis, thus identifying ADGRL3 as a risk gene for SUD. Recursive-partitioning analyses revealed that rs4860437 was the predominant predictive variant. This new methodological approach offers novel insights into higher order predictive interactions and offers a unique opportunity for translational application in the clinical assessment of patients at high risk for SUD.

fMRI classification method with multiple feature fusion based on minimum spanning tree analysis

Resting state functional brain networks have been widely studied in brain disease research. Conventional network analysis methods are hampered by differences in network size, density and normalization. Minimum spanning tree (MST) analysis has been recently suggested to ameliorate these limitations. Moreover, common MST analysis methods involve calculating quantifiable attributes and selecting these attributes as features in the classification. However, a disadvantage of these methods is that information about the topology of the network is not fully considered, limiting further improvement of classification performance. To address this issue, we propose a novel method combining brain region and subgraph features for classification, utilizing two feature types to quantify two properties of the network. We experimentally validated our proposed method using a major depressive disorder (MDD) patient dataset. The results indicated that MSTs of MDD patients were more similar to random networks and exhibited significant differences in certain regions involved in the limbic-cortical-striatal-pallidal-thalamic (LCSPT) circuit, which is considered to be a major pathological circuit of depression. Moreover, we demonstrated that this novel classification method could effectively improve classification accuracy and provide better interpretability. Overall, the current study demonstrated that different forms of feature representation provide complementary information.

Low-frequency and rare variants may contribute to elucidate the genetics of major depressive disorder

Major depressive disorder (MDD) is a common but serious psychiatric disorder with significant levels of morbidity and mortality. Recent genome-wide association studies (GWAS) on common variants increase our understanding of MDD; however, the underlying genetic basis remains largely unknown. Many studies have been proposed to explore the genetics of complex diseases from a viewpoint of the "missing heritability" by considering low-frequency and rare variants, copy-number variations, and other types of genetic variants. Here we developed a novel computational and statistical strategy to investigate the "missing heritability" of MDD. We applied Hamming distance on common, low-frequency, and rare single-nucleotide polymorphism (SNP) sets to measure genetic distance between two individuals, and then built the multi-dimensional scaling (MDS) pictures. Whole-exome genotyping data from a Los Angeles Mexican-American cohort (203 MDD and 196 controls) and a European-ancestry cohort (473 MDD and 497 controls) were examined using our proposed methodology. MDS plots showed very significant separations between MDD cases and healthy controls for low-frequency SNP set (P value < 2.2e-16) and rare SNP set (P value = 7.681e-12). Our results suggested that low-frequency and rare variants may play more significant roles in the genetics of MDD.

PDLIM5 identified by label-free quantitative proteomics as a potential novel biomarker of papillary thyroid carcinoma

In order to better understand the mechanisms underlying the development of papillary thyroid carcinoma (PTC), and to identify new potential biomarkers, high-resolution label-free mass spectrometry was performed on PTC tissues and adjacent normal thyroid tissues from six patients. In this process, 2788 proteins were identified, out of which 49 proteins presented significant differences between PTC tissues and adjacent normal thyroid tissues. Gene ontology revealed that the majority of these proteins are involved in the catalytic activity and binding. We selected three proteins with differential expressions: PDZ and LIM domain 5 (PDLIM5), PDLIM1 and ALDH1A1; Protein expressions were further verified by RT-PCR and western blot. Among these, expression of PDLIM5 and PDLIM1 was up-regulated, while that of ALDH1A1 was down-regulated in PTC tissues. Next, we confirmed their expression through quantitative dot blot (QDB) technique. We found that knockdown of PDLIM5 expression in the B-CPAP cell line could inhibit the migration, invasion and proliferation of PTC cells. In addition, PDLIM5 knockdown reduced Ras and Phospho-ERK1/2 expression. Thus, we suggested that PDLIM5 promotes PTC via activation of the Ras-ERK pathway. Our research provides new molecular insight into the function of PDLIM5, which may assist in studying the mechanism of PTC. In addition, PDLIM5 could be further explored as a potential candidate for PTC treatment.

Machine-Learning Classifier for Patients with Major Depressive Disorder: Multifeature Approach Based on a High-Order Minimum Spanning Tree Functional Brain Network

High-order functional connectivity networks are rich in time information that can reflect dynamic changes in functional connectivity between brain regions. Accordingly, such networks are widely used to classify brain diseases. However, traditional methods for processing high-order functional connectivity networks generally include the clustering method, which reduces data dimensionality. As a result, such networks cannot be effectively interpreted in the context of neurology. Additionally, due to the large scale of high-order functional connectivity networks, it can be computationally very expensive to use complex network or graph theory to calculate certain topological properties. Here, we propose a novel method of generating a high-order minimum spanning tree functional connectivity network. This method increases the neurological significance of the high-order functional connectivity network, reduces network computing consumption, and produces a network scale that is conducive to subsequent network analysis. To ensure the quality of the topological information in the network structure, we used frequent subgraph mining technology to capture the discriminative subnetworks as features and combined this with quantifiable local network features. Then we applied a multikernel learning technique to the corresponding selected features to obtain the final classification results. We evaluated our proposed method using a data set containing 38 patients with major depressive disorder and 28 healthy controls. The experimental results showed a classification accuracy of up to 97.54%.

Investigation of copy number variation in subjects with major depression based on whole-genome sequencing data

BACKGROUND

Despite recent intensive research using genome-wide association studies, the underlying biological basis of major depressive disorder (MDD) still remains unknown. In contrast to genotyping platforms which identify specific variations, whole-genome sequencing (WGS) allows us to detect all private genetic variations within an individual. So far there have been no studies investigating copy number variations (CNVs) in subjects with MDD using WGS data.

METHODS

We obtained complete WGS paired-end reads data of 15 MDD patients and 10 ethnically matched healthy controls. We performed alignments for the sequencing reads and used GASV package to call CNVs including deletion, inversion, translocation and divergence for those subjects.

RESULTS

Our results show that, in the Mexican-American sample, deletion CNVs were significantly richer in MDD cases than healthy controls on each of 23 chromosomes. However, other types of CNVs failed to reach any significance. In the Australian sample, there was no statistically significant difference of CNVs between MDD cases and controls. Furthermore, we found that the Australian group had significantly more deletion CNVs than the Mexican-American group.

LIMITATIONS

High quality WGS costs limited obtaining larger datasets. The GASV package does not currently support duplication or insertion CNVs.

CONCLUSIONS

To our knowledge this is the first time that CNVs detected by WGS data are used to study major depression. The conclusion that deletion CNVs are significantly richer in MDD cases than healthy controls is consistent with the previous finding about recurrent depressive disorder by genome-wide association analysis of CNVs on a large genotyping microarray data.

The PHF21B gene is associated with major depression and modulates the stress response

Major depressive disorder (MDD) affects around 350 million people worldwide; however, the underlying genetic basis remains largely unknown. In this study, we took into account that MDD is a gene-environment disorder, in which stress is a critical component, and used whole-genome screening of functional variants to investigate the 'missing heritability' in MDD. Genome-wide association studies (GWAS) using single- and multi-locus linear mixed-effect models were performed in a Los Angeles Mexican-American cohort (196 controls, 203 MDD) and in a replication European-ancestry cohort (499 controls, 473 MDD). Our analyses took into consideration the stress levels in the control populations. The Mexican-American controls, comprised primarily of recent immigrants, had high levels of stress due to acculturation issues and the European-ancestry controls with high stress levels were given higher weights in our analysis. We identified 44 common and rare functional variants associated with mild to moderate MDD in the Mexican-American cohort (genome-wide false discovery rate, FDR, <0.05), and their pathway analysis revealed that the three top overrepresented Gene Ontology (GO) processes were innate immune response, glutamate receptor signaling and detection of chemical stimulus in smell sensory perception. Rare variant analysis replicated the association of the PHF21B gene in the ethnically unrelated European-ancestry cohort. The TRPM2 gene, previously implicated in mood disorders, may also be considered replicated by our analyses. Whole-genome sequencing analyses of a subset of the cohorts revealed that European-ancestry individuals have a significantly reduced (50%) number of single nucleotide variants compared with Mexican-American individuals, and for this reason the role of rare variants may vary across populations. PHF21b variants contribute significantly to differences in the levels of expression of this gene in several brain areas, including the hippocampus. Furthermore, using an animal model of stress, we found that Phf21b hippocampal gene expression is significantly decreased in animals resilient to chronic restraint stress when compared with non-chronically stressed animals. Together, our results reveal that including stress level data enables the identification of novel rare functional variants associated with MDD.

Whole-genome single nucleotide variant distribution on genomic regions and its relationship to major depression

Recent advances in DNA technologies have provided unprecedented opportunities for biological and medical research. In contrast to current popular genotyping platforms which identify specific variations, whole-genome sequencing (WGS) allows for the detection of all private mutations within an individual. Major depressive disorder (MDD) is a chronic condition with enormous medical, social and economic impacts. Genetic analysis, by identifying risk variants and thereby increasing our understanding of how MDD arises, could lead to improved prevention and the development of new and more effective treatments. Here we investigated the distributions of whole-genome single nucleotide variants (SNVs) on 12 different genomic regions for 25 human subjects using the symmetrised Kullback-Leibler divergence to measure the similarity between their SNV distributions. We performed cluster analysis for MDD patients and ethnically matched healthy controls. The results showed that Mexican-American controls grouped closer; in contrast depressed Mexican-American participants grouped away from their ethnically matched controls. This implies that whole-genome SNV distribution on the genomic regions may be related to major depression.

A latent genetic subtype of major depression identified by whole-exome genotyping data in a Mexican-American cohort

Identifying data-driven subtypes of major depressive disorder (MDD) is an important topic of psychiatric research. Currently, MDD subtypes are based on clinically defined depression symptom patterns. Although a few data-driven attempts have been made to identify more homogenous subgroups within MDD, other studies have not focused on using human genetic data for MDD subtyping. Here we used a computational strategy to identify MDD subtypes based on single-nucleotide polymorphism genotyping data from MDD cases and controls using Hamming distance and cluster analysis. We examined a cohort of Mexican-American participants from Los Angeles, including MDD patients (n=203) and healthy controls (n=196). The results in cluster trees indicate that a significant latent subtype exists in the Mexican-American MDD group. The individuals in this hidden subtype have increased common genetic substrates related to major depression and they also have more anxiety and less middle insomnia, depersonalization and derealisation, and paranoid symptoms. Advances in this line of research to validate this strategy in other patient groups of different ethnicities will have the potential to eventually be translated to clinical practice, with the tantalising possibility that in the future it may be possible to refine MDD diagnosis based on genetic data.

PhenoCurve: capturing dynamic phenotype-environment relationships using phenomics data

Motivation

Phenomics is essential for understanding the mechanisms that regulate or influence growth, fitness, and development. Techniques have been developed to conduct high-throughput large-scale phenotyping on animals, plants and humans, aiming to bridge the gap between genomics, gene functions and traits. Although new developments in phenotyping techniques are exciting, we are limited by the tools to analyze fully the massive phenotype data, especially the dynamic relationships between phenotypes and environments.

Results

We present a new algorithm called PhenoCurve, a knowledge-based curve fitting algorithm, aiming to identify the complex relationships between phenotypes and environments, thus studying both values and trends of phenomics data. The results on both real and simulated data showed that PhenoCurve has the best performance among all the six tested methods. Its application to photosynthesis hysteresis pattern identification reveals new functions of core genes that control photosynthetic efficiency in response to varying environmental conditions, which are critical for understanding plant energy storage and improving crop productivity.

Availability and Implementation

Software is available at phenomics.uky.edu/PhenoCurve.

Contact

chen.jin@uky.edu or kramerd8@cns.msu.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Bayesian logistic regression in detection of gene-steroid interaction for cancer at PDLIM5 locus

The PDZ and LIM domain 5 (PDLIM5) gene may play a role in cancer, bipolar disorder, major depression, alcohol dependence and schizophrenia; however, little is known about the interaction effect of steroid and PDLIM5 gene on cancer. This study examined 47 single-nucleotide polymorphisms (SNPs) within the PDLIM5 gene in the Marshfield sample with 716 cancer patients (any diagnosed cancer, excluding minor skin cancer) and 2848 noncancer controls. Multiple logistic regression model in PLINK software was used to examine the association of each SNP with cancer. Bayesian logistic regression in PROC GENMOD in SAS statistical software, ver. 9.4 was used to detect gene- steroid interactions influencing cancer. Single marker analysis using PLINK identified 12 SNPs associated with cancer (P< 0.05); especially, SNP rs6532496 revealed the strongest association with cancer (P = 6.84 × 10⁻³); while the next best signal was rs951613 (P = 7.46 × 10⁻³). Classic logistic regression in PROC GENMOD showed that both rs6532496 and rs951613 revealed strong gene-steroid interaction effects (OR=2.18, 95% CI=1.31-3.63 with P = 2.9 × 10⁻³ for rs6532496 and OR=2.07, 95% CI=1.24-3.45 with P = 5.43 × 10⁻³ for rs951613, respectively). Results from Bayesian logistic regression showed stronger interaction effects (OR=2.26, 95% CI=1.2-3.38 for rs6532496 and OR=2.14, 95% CI=1.14-3.2 for rs951613, respectively). All the 12 SNPs associated with cancer revealed significant gene-steroid interaction effects (P < 0.05); whereas 13 SNPs showed gene-steroid interaction effects without main effect on cancer. SNP rs4634230 revealed the strongest gene-steroid interaction effect (OR=2.49, 95% CI=1.5-4.13 with P = 4.0 × 10⁻⁴ based on the classic logistic regression and OR=2.59, 95% CI=1.4-3.97 from Bayesian logistic regression; respectively). This study provides evidence of common genetic variants within the PDLIM5 gene and interactions between PLDIM5 gene polymorphisms and steroid use influencing cancer.

A novel strategy for clustering major depression individuals using whole-genome sequencing variant data

Major depressive disorder (MDD) is highly prevalent, resulting in an exceedingly high disease burden. The identification of generic risk factors could lead to advance prevention and therapeutics. Current approaches examine genotyping data to identify specific variations between cases and controls. Compared to genotyping, whole-genome sequencing (WGS) allows for the detection of private mutations. In this proof-of-concept study, we establish a conceptually novel computational approach that clusters subjects based on the entirety of their WGS. Those clusters predicted MDD diagnosis. This strategy yielded encouraging results, showing that depressed Mexican-American participants were grouped closer; in contrast ethnically-matched controls grouped away from MDD patients. This implies that within the same ancestry, the WGS data of an individual can be used to check whether this individual is within or closer to MDD subjects or to controls. We propose a novel strategy to apply WGS data to clinical medicine by facilitating diagnosis through genetic clustering. Further studies utilising our method should examine larger WGS datasets on other ethnical groups.

Development of depression in survivors of childhood and adolescent cancer: a multi-level life course conceptual framework

As therapeutic and supportive care interventions become increasingly effective, growing numbers of childhood and adolescent cancer survivors face a myriad of physical and psychological sequelae secondary to their disease and treatment. Mental health issues, in particular, present a significant problem in this unique patient population, with depression affecting a sizable number of childhood and adolescent cancer survivors. Multiple key determinants impact a survivor's risk of developing depression, with variables traversing across biologic, individual, family, community, and global levels, as well as spanning throughout the life course of human development from the preconception and prenatal periods to adulthood. A multi-level life course conceptual model offers a valuable framework to identify and organize the diverse variables that modulate the risk of developing depression in survivors of childhood and adolescent cancer. This review describes the first multi-level life course perspective applied to development of depression in childhood and adolescent cancer survivors. This conceptual framework may be used to guide the investigation of mental health interventions for SCACs to ensure that key determinants of depression occurrence are adequately addressed across various levels and throughout the life trajectory.

Single-nucleotide variant proportion in genes: a new concept to explore major depression based on DNA sequencing data

Major depressive disorder (MDD) is a common psychiatric illness with significant medical and socioeconomic impact. Genetic factors are likely to play important roles in the development of this condition. DNA sequencing technology has the ability to identify all private genetic mutations and provides new channels for studying the biology of MDD. In this proof-of-concept study we proposed a novel concept, single-nucleotide variant proportion (SNVP), to investigate MDD based on whole-genome sequencing (WGS) data. Our SNVP-based approach can be used to test newly found candidate genes as a complement to genome-wide genotyping analysis. Furthermore, we performed cluster analysis for MDD patients and ethnically matched healthy controls, and found that clusters based on SNVP may predict MDD diagnosis. Our results suggest that SNVP may be used as a potential biomarker associated with major depression. Our methodology could be a valuable predictive/diagnostic tool as one can test whether a new subject falls within or close to an existing MDD cluster. Advances in this study design have the potential to personalized treatments and could include the ability to diagnose patients based on their full or part DNA sequencing data.

Building a genetic risk model for bipolar disorder from genome-wide association data with random forest algorithm

A genetic risk score could be beneficial in assisting clinical diagnosis for complex diseases with high heritability. With large-scale genome-wide association (GWA) data, the current study constructed a genetic risk model with a machine learning approach for bipolar disorder (BPD). The GWA dataset of BPD from the Genetic Association Information Network was used as the training data for model construction, and the Systematic Treatment Enhancement Program (STEP) GWA data were used as the validation dataset. A random forest algorithm was applied for pre-filtered markers, and variable importance indices were assessed. 289 candidate markers were selected by random forest procedures with good discriminability; the area under the receiver operating characteristic curve was 0.944 (0.935–0.953) in the training set and 0.702 (0.681–0.723) in the STEP dataset. Using a score with the cutoff of 184, the sensitivity and specificity for BPD was 0.777 and 0.854, respectively. Pathway analyses revealed important biological pathways for identified genes. In conclusion, the present study identified informative genetic markers to differentiate BPD from healthy controls with acceptable discriminability in the validation dataset. In the future, diagnosis classification can be further improved by assessing more comprehensive clinical risk factors and jointly analysing them with genetic data in large samples.

Polymorphisms in PDLIM5 gene are associated with alcohol dependence, type 2 diabetes, and hypertension

The PDZ and LIM domain 5 (PDLIM5) gene may play a role in alcohol dependence (AD), bipolar disorder, and major depressive disorder; however, no study has identified shared genetic variants within PDLIM5 gene among AD, type 2 diabetes (T2D), and hypertension. This study investigated the association of 72 single nucleotide polymorphism (SNPs) with AD (1066 AD cases and 1278 controls) in the Study of Addiction - Genetics and Environment (SAGE) sample and 47 SNPs with T2D (878 cases and 2686 non-diabetic) and hypertension (825 cases and 2739 non-hypertensive) in the Marshfield sample. Multiple logistic regression models in PLINK software were used to examine the associations of genetic variants with AD, T2D, and hypertension and SNP x alcohol consumption interactions for T2D and hypertension. Twenty-five SNPs were associated with AD in the SAGE sample (p < 0.05); rs1048627 showed the strongest association with AD (p = 5.53 × 10^-4). Of the 25 SNPs, 5 SNPs showed associations with both AD in the SAGE sample and T2D in the Marshfield sample (top SNP rs11097432 with p = 0.00107 for T2D and p = 0.0483 for AD) while 6 SNPs showed associations with both AD in the SAGE sample and hypertension in the Marshfield sample (top SNP rs12500426 with p = 0.0119 for hypertension and p = 1.51 × 10^-3 for AD). SNP (rs6532496) showed significant interaction with alcohol consumption for hypertension. Our results showed that several genetic variants in PDLIM5 gene influence AD, T2D and hypertension. These findings offer the potential for new insights into the pathogenesis of AD, T2D, and hypertension.

Affective disorders as potential complication of anti-acne treatment with isotretinoin: A case series

OBJECTIVE

To analyse cases of 9 patients (18-27 yo) who were consequently admitted to our department and treated with affective disorders (AD) while undergoing isotretinoin (INN) therapy.

METHODS

A semi-structured questionnaire designed by the authors was used to analyse many variables related to demographic characteristics, dermatologic and psychiatrics symptoms, AD course and treatment, family history of mental disorders, building on medical histories of patients and their families, and available medical records.

RESULTS

Patients were diagnosed (DSM-IV-TR) with: a major depressive episode (4 patients), a recurrent major depressive episode (3), a bipolar mixed episode (1), and rapid cycling bipolar I disorder (1). The mean time from the first use of INN to: I. the onset of mental disorders was approximately 2 months (1-6 months), II. a visit with a psychiatrist was about 12 months (1-38 months). The predictors of occurrence of AD included a family history of AD and a prior episode of mental disorders. The onset of AD was in most cases preceded by prodromal symptoms such as headaches, sleep disorders, fatigue, drowsiness, or general weakness. Five patients reported suicidal ideation, four patients showed suicidal tendencies, and two persons attempted to commit suicide during the treatment.

CONCLUSIONS

Psychiatrists should pay special attention to isotretinoin as a drug that may trigger episodes of AD, particularly in patients with a family history of AD or prior episodes of mental disorders. Isotretinoin therapy of patients with acne and a family history of AD or prior episodes of mental disorders requires special care and, if symptoms of depression develop or worsen during the INN treatment, collaboration between a dermatologist and a psychiatrist is needed.

Meta-analysis of the COMT Val158Met polymorphism in major depressive disorder: the role of gender

OBJECTIVES

Many studies have reported an association of the COMT Val158Met polymorphism and major depressive disorder (MDD), although with conflicting results. The role of gender is a possible modulator. To overcome the problem of poor sample size detecting genes of small effect, we perform a meta-analysis of the current literature, investigating the influence of the COMT Val158Met polymorphism on the pathogenesis of MDD, with a major focus on the effect of gender.

METHODS

Out of 977 retrieved articles, 21 included case-control studies allowed the analysis of 9005 patients with MDD and 12,095 controls. Allelic and genotypic pooled odds ratios (OR) were calculated for the total sample and gender-subgroups.

RESULTS

In the absence of publication bias, allelic and genotypic analyses showed no significant association in the total sample, as well as in gender-specific subgroups. Sensitivity analysis did not alter the ORs.

CONCLUSIONS

The results imply a complex nature of the genotype × phenotype interaction. Further studies of the COMT gene or the locus remain to be justified given the important positional and functional relevance and the plethora of gender-specific findings. A possible way to further dissect this topic is shifting the focus to gene-based or genome-wide analyses of intermediate phenotypes.

APOE*E2 allele delays age of onset in PSEN1 E280A Alzheimer's disease

Alzheimer's disease (AD) age of onset (ADAOO) varies greatly between individuals, with unique causal mutations suggesting the role of modifying genetic and environmental interactions. We analyzed ~50 000 common and rare functional genomic variants from 71 individuals of the 'Paisa' pedigree, the world's largest pedigree segregating a severe form of early-onset AD, who were affected carriers of the fully penetrant E280A mutation in the presenilin-1 (PSEN1) gene. Affected carriers with ages at the extremes of the ADAOO distribution (30s-70s age range), and linear mixed-effects models were used to build single-locus regression models outlining the ADAOO. We identified the rs7412 (APOE*E2 allele) as a whole exome-wide ADAOO modifier that delays ADAOO by ~12 years (β=11.74, 95% confidence interval (CI): 8.07-15.41, P=6.31 × 10(-8), PFDR=2.48 × 10(-3)). Subsequently, to evaluate comprehensively the APOE (apolipoprotein E) haplotype variants (E1/E2/E3/E4), the markers rs7412 and rs429358 were genotyped in 93 AD affected carriers of the E280A mutation. We found that the APOE*E2 allele, and not APOE*E4, modifies ADAOO in carriers of the E280A mutation (β=8.24, 95% CI: 4.45-12.01, P=3.84 × 10(-5)). Exploratory linear mixed-effects multilocus analysis suggested that other functional variants harbored in genes involved in cell proliferation, protein degradation, apoptotic and immune dysregulation processes (i.e., GPR20, TRIM22, FCRL5, AOAH, PINLYP, IFI16, RC3H1 and DFNA5) might interact with the APOE*E2 allele. Interestingly, suggestive evidence as an ADAOO modifier was found for one of these variants (GPR20) in a set of patients with sporadic AD from the Paisa genetic isolate. This is the first study demonstrating that the APOE*E2 allele modifies the natural history of AD typified by the age of onset in E280A mutation carriers. To the best of our knowledge, this is the largest analyzed sample of patients with a unique mutation sharing uniform environment. Formal replication of our results in other populations and in other forms of AD will be crucial for prediction, follow-up and presumably developing new therapeutic strategies for patients either at risk or affected by AD.

CRMPs: critical molecules for neurite morphogenesis and neuropsychiatric diseases

Neuronal polarity and spatial rearrangement of neuronal processes are central to the development of all mature nervous systems. Recent studies have highlighted the dynamic expression of Collapsin-Response-Mediator Proteins (CRMPs) in neuronal dendritic/axonal compartments, described their interaction with cytoskeleton proteins, identified their ability to activate L- and N-type voltage-gated calcium channels (VGCCs) and delineated their crucial role as signaling molecules essential for neuron differentiation and neural network development and maintenance. In addition, evidence obtained from genome-wide/genetic linkage/proteomic/translational approaches revealed that CRMP expression is altered in human pathologies including mental (schizophrenia and mood disorders) and neurological (Alzheimer's, prion encephalopathy, epilepsy and others) disorders. Changes in CRMPs levels have been observed after psychotropic treatments, and disrupting CRMP2 binding to calcium channels blocked neuropathic pain. These observations, altogether with those obtained from genetically modified mice targeting individual CRMPs and RNA interference approaches, pave the way for considering CRMPs as potential early disease markers and modulation of their activity as therapeutic strategy for disorders associated with neurite abnormalities.

T2D and Depression Risk Gene Proteasome Modulator 9 is Linked to Insomnia

Insomnia increases type-2 diabetes (T2D) risk. The 12q24 locus is linked to T2D, depression, bipolar disorder and anxiety. At the 12q24 locus, the Proteasome-Modulator 9 (PSMD9) single nucleotide polymorphisms (SNPs) rs74421874 [intervening sequence (IVS) 3+nt460-G>A], rs3825172 (IVS3+nt437-C>T) and rs14259 (E197G-A>G) are linked to: T2D, depression, anxiety, maturity-onset-diabetes-of the young 3/MODY3, obesity, waist circumference, hypertension, hypercholesterolemia, T2D-macrovascular disease, T2D-microvascular disease, T2D-neuropathy, T2D-carpal-tunnel syndrome, T2D-nephropathy, T2D-retinopathy and non-diabetic retinopathy. PSMD9 SNP rs1043307/rs14259 (E197G-A>G) plays a role in anti-depressant therapy response, depression and schizophrenia. We aimed at determining PSMD9 rs74421874/rs3825172/rs14259 SNPs potential linkage to primary insomnia and sleep hours in T2D families. We recruited 200 Italian T2D families phenotyping them for primary insomnia and sleep hours per night. PSMD9-T2D-risk SNPs rs74421874/rs3825172 and rs1043307/rs14259 were tested for linkage with insomnia and sleep hours. Non-parametric-linkage analysis, linkage-disequilibrium-model analysis, single-SNP analysis, cluster-based-parametric analysis, quantitative-trait and variant-component analysis were performed using Merlin software. To validate data, 1000 replicates were executed for the significant non-parametric data. PSMD9 rs74421874 (IVS3+nt460-G>A), rs3825172 (IVS3+nt437-C>T) and rs1043307/rs14259 (E197G-A>G) SNPs are linked to insomnia in our Italian families.

The ups and downs of modelling mood disorders in rodents

The wide spectrum of disruptions that characterizes major depressive disorder (MDD) and bipolar disorder (BD) highlights the difficulties researchers are posed with as they try to mimic these disorders in the laboratory. Nonetheless, numerous attempts have been made to create rodent models of mood disorders or at least models of the symptoms of MDD and BD. Present antidepressants are all descendants of the serendipitous findings in the 1950s that the monoamine oxidase inhibitor iproniazid and the tricyclic antidepressant imipramine were effective antidepressants. Thus, the need for improved animal models to provide insights into the neuropathology underlying the disease is critical. Such information is in turn crucial for identifying new antidepressants and mood stabilisers. Currently, there is a shift away from traditional animal models to more focused research dealing with an endophenotype-style approach, genetic models, and incorporation of new findings from human neuroimaging and genetic studies. Such approaches are opening up more tractable avenues for understanding the neurobiological and genetic bases of these disorders. Further, such models promise to yield better translational animal models and hence more fruitful therapeutic targets. This overview focuses on such animal models and tests and how they can be used to assess MDD and BD in rodents.

Single nucleotide polymorphism creating a variable upstream open reading frame regulates glucocorticoid receptor expression

The glucocorticoid and mineralocorticoid receptors are known to play a crucial role in cellular responses to acute and chronic stress conditions. However, the influence of genetic variants and regulatory mechanisms within the glucocorticoid and mineralocorticoid receptor genes NR3C1 and NR3C2 is still incompletely understood. We therefore investigated putative upstream open reading frames, a motif regulating gene expression, from the 5' untranslated regions of the predominant human glucocorticoid receptor gene NR3C1 isoform alpha variant 1 and from the human mineralocorticoid receptor NR3C2 variants 1 and 2. The in silico analysis displayed one SNP (rs10482612), being present heterozygously in about 1.2% of the world population and 1.8% of the European population (according to the NCBI database), whose minor allele 'A' creates an upstream start codon. Our functional analysis performed by reporter gene assay and quantitative real-time PCR confirmed that the minor allele 'A' of the SNP rs10482612 can indeed alter protein activity of the subsequent gene during baseline conditions and cellular stress by creating a functional uORF in the 5'UTR of the NR3C1 transcript variant 1.

An overview of the neurobiology of suicidal behaviors as one meta-system

Suicidal behaviors (SB) may be regarded as the outmost consequence of mental illnesses, or as a distinct entity per se. Regardless, the consequences of SB are very large to both society and affected individuals. The path leading to SB is clearly a complex one involving interactions between the subject's biology and environmental influences throughout life. With the aim to generate a representative and diversified overview of the different neurobiological components hypothesized or shown implicated across the entire SB field up to date by any approach, we selected and compiled a list of 212 gene symbols from the literature. An increasing number of novel gene (products) have been introduced as candidates, with half being implicated in SB in only the last 4 years. These candidates represent different neuro systems and functions and might therefore be regarded as competing or redundant explanations. We then adopted a unifying approach by treating them all as parts of the same meta-system, using bioinformatic tools. We present a network of all components connected by physical protein-protein interactions (the SB interactome). We proceeded by exploring the differences between the highly connected core (~30% of the candidate genes) and its peripheral parts, observing more functional homogeneity at the core, with multiple signal transduction pathways and actin-interacting proteins connecting a subset of receptors in nerve cell compartments as well as development/morphology phenotypes and the stress-sensitive synaptic plasticity processes of long term potentiation/depression. We suggest that SB neurobiology might also be viewed as one meta-system and perhaps be explained as intrinsic unbalances acting within the core or as imbalances arising between core and specific peripheral components.

Coordinated messenger RNA/microRNA changes in fibroblasts of patients with major depression

BACKGROUND

Peripheral biomarkers for major psychiatric disorders have been an elusive target for the last half a century. Dermal fibroblasts are a simple, relevant, and much underutilized model for studying molecular processes of patients with affective disorders, as they share considerable similarity of signal transduction with neuronal tissue.

METHODS

Cultured dermal fibroblast samples from patients with major depressive disorder (MDD) and matched control subjects (n = 16 pairs, 32 samples) were assayed for genome-wide messenger RNA (mRNA) expression using microarrays. In addition, a simultaneous quantitative polymerase chain reaction-based assessment of >1000 microRNA (miRNA) species was performed. Finally, to test the relationship between the mRNA-miRNA expression changes, the two datasets were correlated with each other.

RESULTS

Our data revealed that MDD fibroblasts, when compared with matched control subjects, showed a strong mRNA gene expression pattern change in multiple molecular pathways, including cell-to-cell communication, innate/adaptive immunity, and cell proliferation. Furthermore, the same patient fibroblasts showed altered expression of a distinct panel of 38 miRNAs, which putatively targeted many of the differentially expressed mRNAs. The miRNA-mRNA expression changes appeared to be functionally connected, as the majority of the miRNA and mRNA changes were in the opposite direction.

CONCLUSIONS

Our data suggest that combined miRNA-mRNA assessments are informative about the disease process and that analyses of dermal fibroblasts might lead to the discovery of promising peripheral biomarkers of MDD that could be potentially used to aid the diagnosis and allow mechanistic testing of disturbed molecular pathways.

CREB1 gene polymorphisms combined with environmental risk factors increase susceptibility to major depressive disorder (MDD)

Major depressive disorder (MDD) is one of the most severe psychiatric disorders. The objective of this study was to explore the effects of CREB1 gene polymorphisms on risk of developing MDD and the joint effects of gene-environment interactions. Genotyping was performed by Taqman allelic discrimination assay among 586 patients and 586 healthy controls. A significant impact on rs6740584 genotype distribution was found for childhood trauma (P = 0.015). We did not find an association of CREB1 polymorphisms with MDD susceptibility. However, we found a significantly increased risk associated with the interactions of CREB1 polymorphisms and drinking (OR = 11.67, 95% CI = 2.52-54.18; OR = 11.52, 95% CI = 2.55-51.95 for rs11904814; OR = 4.18, 95% CI = 1.87-9.38; OR = 5.02, 95% CI = 2.27-11.14 for rs6740584; OR = 7.58, 95% CI = 2.05-27.98; OR = 7.59, 95% CI = 2.12-27.14 for rs2553206; OR = 8.37, 95% CI = 3.02-23.23; OR = 7.84, 95% CI = 2.93-20.98 for rs2551941). We also noted that CREB polymorphisms combined with family harmony and childhood trauma conferred increased susceptibility for MDD. In conclusion, polymorphisms in the CREB gene may not be independently associated with MDD risk, but they are likely to confer increased susceptibility by interacting with environmental risk factors in the Chinese population.