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Subcortical brain structures are involved in developmental, psychiatric and neurological disorders. Here we performed genome-wide association studies meta-analyses of intracranial and nine subcortical brain volumes (brainstem, caudate nucleus, putamen, hippocampus, globus pallidus, thalamus, nucleus accumbens, amygdala and the ventral diencephalon) in 74,898 participants of European ancestry. We identified 254 independent loci associated with these brain volumes, explaining up to 35% of phenotypic variance. We observed gene expression in specific neural cell types across differentiation time points, including genes involved in intracellular signaling and brain aging-related processes. Polygenic scores for brain volumes showed predictive ability when applied to individuals of diverse ancestries. We observed causal genetic effects of brain volumes with Parkinson's disease and attention-deficit/hyperactivity disorder. Findings implicate specific gene expression patterns in brain development and genetic variants in comorbid neuropsychiatric disorders, which could point to a brain substrate and region of action for risk genes implicated in brain diseases., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Cellular crosstalk is an essential process influenced by numerous factors, including secreted vesicles that transfer nucleic acids, lipids, and proteins between cells. Extracellular vesicles (EVs) have been the center of many studies focusing on neurodegenerative disorders, but whether EVs display cell-type-specific features for cellular crosstalk during neurodevelopment is unknown. Here, using human-induced pluripotent stem cell-derived cerebral organoids, neural progenitors, neurons, and astrocytes, we identify heterogeneity in EV protein content and dynamics in a cell-type-specific and time-dependent manner. Our results support the trafficking of key molecules via EVs in neurodevelopment, such as the transcription factor YAP1, and their localization to differing cell compartments depending on the EV recipient cell type. This study sheds new light on the biology of EVs during human brain development., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: The global mortality rate resulting from HIV-associated cryptococcal disease is remarkably elevated, particularly in severe cases with dissemination to the lungs and central nervous system (CNS). Regrettably, there is a dearth of predictive analysis regarding long-term survival, and few studies have conducted longitudinal follow-up assessments for comparing anti-HIV and antifungal treatments., Methods: A cohort of 83 patients with HIV-related disseminated cryptococcosis involving the lung and CNS was studied for 3 years to examine survival. Comparative analysis of clinical and immunological parameters was performed between deceased and surviving individuals. Subsequently, multivariate Cox regression models were utilized to validate mortality predictions at 12, 24, and 36 months., Results: Observed plasma cytokine levels before treatment were significantly lower for IL-1RA (p < 0.001) and MCP-1 (p < 0.05) when in the survivor group. Incorporating plasma levels of IL-1RA, IL-6, and high-risk CURB-65 score demonstrated the highest area under curve (AUC) value (0.96) for predicting 1-year mortality. For 1-, 2- and 3-year predictions, the single-factor model with IL-1RA demonstrated superior performance compared to all multiple-variate models (AUC = 0.95/0.78/0.78)., Conclusions: IL-1RA is a biomarker for predicting 3-year survival. Further investigations to explore the pathogenetic role of IL-1RA in HIV-associated disseminated cryptococcosis and as a potential therapeutic target are warranted., (© 2024. The Author(s).)

Subcortical brain structures are involved in developmental, psychiatric and neurological disorders. We performed GWAS meta-analyses of intracranial and nine subcortical brain volumes (brainstem, caudate nucleus, putamen, hippocampus, globus pallidus, thalamus, nucleus accumbens, amygdala and, for the first time, the ventral diencephalon) in 74,898 participants of European ancestry. We identified 254 independent loci associated with these brain volumes, explaining up to 35% of phenotypic variance. We observed gene expression in specific neural cell types across differentiation time points, including genes involved in intracellular signalling and brain ageing-related processes. Polygenic scores for brain volumes showed predictive ability when applied to individuals of diverse ancestries. We observed causal genetic effects of brain volumes with Parkinson's disease and ADHD. Findings implicate specific gene expression patterns in brain development and genetic variants in comorbid neuropsychiatric disorders, which could point to a brain substrate and region of action for risk genes implicated in brain diseases., Competing Interests: IA received speaker’s honorarium Lundbeck; OAA is a consultant to Cortechs.ai and Precision Health, speaker’s honorarium from Lundbeck, Janssen, Otsuka, Sunovion; HB is an Advisory Board Member or Consultant to Biogen, Eisai, Eli Lilly, Roche, Skin2Neuron, Cranbrook Care and Montefiore Homes; CRKC has received past partial research support from Biogen, Inc. (Boston, USA) for work unrelated to the topic of this manuscript; AMD is the Principal Investigator of a research agreement between General Electric Healthcare and the University of California, San Diego (UCSD); he is a Founder of and hold equity in CorTechs Labs, Inc. I am a member of the Scientific Advisory Board of Human Longevity, Inc., and the Mohn Medical Imaging and Visualization Center in Bergen, Norway. The terms of these arrangements have been reviewed and approved by UCSD in accordance with its conflict-of-interest policies; BF has received educational speaking fees from Medice; HJG has received travel grants and speakers honoraria from Fresenius Medical Care, Neuraxpharm, Servier and Janssen Cilag as well as research funding from Fresenius Medical Care; DPH is a full time employee of Genentech, Inc; NH is a shareholder various manufacturers of medical technology; AM-L has received consultant fees from Daimler und Benz Stiftung, EPFL Brain Mind Institute, Fondation FondaMental, Hector Stiftung II, Invisio, Janssen-Cilag GmbH, Lundbeck A/S, Lundbeckfonden, Lundbeck Int. Neuroscience Foundation, Neurotorium, MedinCell, The LOOP Zürich, University Medical Center Utrecht, University of Washington, Verein für Mentales Wohlbefinden, von Behring-Röntgen-Stiftung; speaker fees from Ärztekammer Nordrhein, Caritas, Clarivate, Dt. Gesellschaft für Neurowissenschaftliche Begutachtung, Gentner Verlag, Landesärztekammer Baden-Württemberg, LWL Bochum, Northwell Health, Ruhr University Bochum, Penn State University, Society of Biological Psychiatry, University Prague, Vitos Klinik Rheingau and editorial and/or author fees fromAmerican Association for the Advancement of Science, ECNP, Servier Int., Thieme Verlag; WN is founder of Quantib BV and was scientific lead of Quantib BV until Jan 31, 2023; MMN has received fees for membership in an advisory board from HMG Systems Engineering GmbH (Fürth, Germany), for membership in the Medical-Scientific Editorial Office of the Deutsches Ärzteblatt, and for serving as a consultant for EVERIS Belgique SPRL in a project of the European Commission (REFORM/SC2020/029). MMN receives salary payments from Life & Brain GmbH and holds shares in Life & Brain GmbH. All these concerned activities outside the submitted work; BMP serves on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson; AJS receives support from multiple NIH grants (P30 AG010133, P30 AG072976, R01 AG019771, R01 AG057739, U19 AG024904, R01 LM013463, R01 AG068193, T32 AG071444, U01 AG068057, U01 AG072177, and U19 AG074879). He has also received support from Avid Radiopharmaceuticals, a subsidiary of Eli Lilly (in kind contribution of PET tracer precursor); Bayer Oncology (Scientific Advisory Board); Eisai (Scientific Advisory Board); Siemens Medical Solutions USA, Inc. (Dementia Advisory Board); NIH NHLBI (MESA Observational Study Monitoring Board); Springer-Nature Publishing (Editorial Office Support as Editor-in-Chief, Brain Imaging and Behavior); MSreceived funding from Pfizer Inc. for a project not related to this research; ES received speaker fees from bfd buchholz fachinformationsdienst gmbh; PMT receives partial research support from Biogen, Inc., for research unrelated to this manuscript; MWW serves on Editorial Boards for Alzheimer’s & Dementia, and the Journal for Prevention of Alzheimer’s disease. He has served on Advisory Boards for Acumen Pharmaceutical, Alzheon, Inc., Cerecin, Merck Sharp & Dohme Corp., and NC Registry for Brain Health. He also serves on the USC ACTC grant which receives funding from Eisai for the AHEAD study. MWW has provided consulting to Boxer Capital, LLC, Cerecin, Inc., Clario, Dementia Society of Japan, Eisai, Guidepoint, Health and Wellness Partners, Indiana University, LCN Consulting, Merck Sharp & Dohme Corp., NC Registry for Brain Health, Prova Education, T3D Therapeutics, University of Southern California (USC), and WebMD. MWW has acted as a speaker/lecturer for China Association for Alzheimer’s Disease (CAAD) and Taipei Medical University, as well as a speaker/lecturer with academic travel funding provided by: AD/PD Congress, Cleveland Clinic, CTAD Congress, Foundation of Learning; Health Society (Japan), INSPIRE Project; U. Toulouse, Japan Society for Dementia Research, and Korean Dementia Society, Merck Sharp & Dohme Corp., National Center for Geriatrics and Gerontology (NCGG; Japan), University of Southern California (USC). MWW holds stock options with Alzeca, Alzheon, Inc., ALZPath, Inc., and Anven. MWW received support for his research from the following funding sources: National Institutes of Health (NIH)/NINDS/National Institute on Aging (NIA), Department of Defense (DOD), California Department of Public Health (CDPH), University of Michigan, Siemens, Biogen, Hillblom Foundation, Alzheimer’s Association, Johnson & Johnson, Kevin and Connie Shanahan, GE, VUmc, Australian Catholic University (HBI-BHR), The Stroke Foundation, and the Veterans Administration; AIC is currently employed by the Regeneron Genetics Center, a wholly-owned subsidiary of Regeneron Pharmaceuticals, Inc., and may hold Regeneron stock or stock options. All other authors declare no competing interests.

Severe stress exposure increases the risk of stress-related disorders such as major depressive disorder (MDD). An essential characteristic of MDD is the impairment of social functioning and lack of social motivation. Chronic social defeat stress is an established animal model for MDD research, which induces a cascade of physiological and behavioral changes. Current markerless pose estimation tools allow for more complex and naturalistic behavioral tests. Here, we introduce the open-source tool DeepOF to investigate the individual and social behavioral profile in mice by providing supervised and unsupervised pipelines using DeepLabCut-annotated pose estimation data. Applying this tool to chronic social defeat in male mice, the DeepOF supervised and unsupervised pipelines detect a distinct stress-induced social behavioral pattern, which was particularly observed at the beginning of a novel social encounter and fades with time due to habituation. In addition, while the classical social avoidance task does identify the stress-induced social behavioral differences, both DeepOF behavioral pipelines provide a clearer and more detailed profile. Moreover, DeepOF aims to facilitate reproducibility and unification of behavioral classification by providing an open-source tool, which can advance the study of rodent individual and social behavior, thereby enabling biological insights and, for example, subsequent drug development for psychiatric disorders., (© 2023. The Author(s).)

Genome-wide gene expression analyses are invaluable tools for studying biological and disease processes, allowing a hypothesis-free comparison of expression profiles. Traditionally, transcriptomic analysis has focused on gene-level effects found by differential expression. In recent years, network analysis has emerged as an important additional level of investigation, providing information on molecular connectivity, especially for diseases associated with a large number of linked effects of smaller magnitude, like neuropsychiatric disorders. Here, we describe how combined differential expression and prior-knowledge-based differential network analysis can be used to explore complex datasets. As an example, we analyze the transcriptional responses following administration of the glucocorticoid/stress receptor agonist dexamethasone in 8 mouse brain regions important for stress processing. By applying a combination of differential network- and expression-analyses, we find that these explain distinct but complementary biological mechanisms of the glucocorticoid responses. Additionally, network analysis identifies new differentially connected partners of risk genes and can be used to generate hypotheses on molecular pathways affected. With DiffBrainNet (http://diffbrainnet.psych.mpg.de), we provide an analysis framework and a publicly available resource for the study of the transcriptional landscape of the mouse brain which can identify molecular pathways important for basic functioning and response to glucocorticoids in a brain-region specific manner., Competing Interests: The authors declare no conflict of interest., (© 2022 The Authors.)

Purpose: Bisoprolol is a widely used beta-blocker in patients with cardiovascular diseases. As with other beta-blockers, there is variability in response to bisoprolol, but the underlying reasons for this have not been clearly elucidated. Our aim was to investigate genetic factors that affect bisoprolol pharmacokinetics (PK) and pharmacodynamics (PD), and potentially the clinical outcomes., Patients and Methods: Patients with non-ST elevation acute coronary syndrome were recruited prospectively on admission to hospital and followed up for up to 2 years. Patients from this cohort who were on treatment with bisoprolol, at any dose, had bisoprolol adherence data and a plasma sample, one month after discharge from index hospitalisation were included in the study. Individual bisoprolol clearance values were estimated using population pharmacokinetic modeling. Genome-wide association analysis after genotyping was undertaken using an Illumina HumanOmniExpressExome-8 v1.0 BeadChip array, while CYP2D6 copy number variations were determined by PCR techniques and phenotypes for CYP2D6 and CYP3A were inferred from the genotype. GWAS significant SNPs were analysed for heart rate response to bisoprolol in an independent cohort of hypertensive subjects., Results: Six hundred twenty-two patients on bisoprolol underwent both PK and genome wide analysis. The mean (IQR) of the estimated clearance in this population was 13.6 (10.0-18.0) L/h. Bisoprolol clearance was associated with rs11029955 (p=7.17×10 -9 ) mapped to the region of coiled-coil domain containing 34 region (CCDC34) on chromosome 11, and with rs116702638 (p=2.54×10 -8 ). Each copy of the minor allele of rs11029955 was associated with 2.2 L/h increase in clearance. In an independent cohort of hypertensive subjects, rs11029955 was associated with 24-hour heart rate response to 4-week treatment with bisoprolol (p= 9.3×10 -5 ), but not with rs116702638., Conclusion: A novel locus on the chromosomal region 11p14.1 was associated with bisoprolol clearance in a real-world cohort of patients and was validated in independent cohort with a pharmacodynamic association., Competing Interests: MP has received partnership funding for the following: MRC Clinical Pharmacology Training Scheme (co-funded by MRC and Roche, UCB, Eli Lilly and Novartis); a PhD studentship jointly funded by EPSRC and Astra Zeneca; and grant funding from Vistagen Therapeutics. He also has unrestricted educational grant support for the UK Pharmacogenetics and Stratified Medicine Network from Bristol-Myers Squibb. He has developed an HLA genotyping panel with MC Diagnostics, but does not benefit financially from this. He is part of the IMI Consortium ARDAT (www.ardat.org). None of the funding MP received is related to the current paper. RMT reports grants from MRC and Health Education England Genomics Education Programme during the conduct of the study. The views expressed in this publication are those of the authors and not necessarily those of HEE GEP. The authors report no other conflicts of interest in this work., (© 2022 Fontana et al.)

Recent genome-wide association studies have identified over 230 genetic risk loci for multiple sclerosis. Current experimental autoimmune encephalomyelitis (EAE) models requiring active induction of disease may not be optimally suited for the characterization of the function of these genes. We have thus used gene expression profiling to study whether spontaneous opticospinal EAE (OSE) or MOG-induced EAE mirrors the genetic contribution to the pathogenesis of multiple sclerosis more faithfully. To this end, we compared gene expression in OSE and MOG EAE models and analyzed the relationship of both models to human multiple sclerosis risk genes and T helper cell biology. We observed stronger gene expression changes and an involvement of more pathways of the adaptive immune system in OSE than MOG EAE. Furthermore, we demonstrated a more extensive enrichment of human MS risk genes among transcripts differentially expressed in OSE than was the case for MOG EAE. Transcripts differentially expressed only in diseased OSE mice but not in MOG EAE were significantly enriched for T helper cell-specific transcripts. These transcripts are part of immune-regulatory pathways. The activation of the adaptive immune system and the enrichment of both human multiple sclerosis risk genes and T helper cell-specific transcripts were also observed in OSE mice showing only mild disease signs. These expression changes may, therefore, be indicative of processes at disease onset. In summary, more human multiple sclerosis risk genes were differentially expressed in OSE than was observed for MOG EAE, especially in T H 1 cells. When studying the functional role of multiple sclerosis risk genes and pathways during disease onset and their interactions with the environment, spontaneous OSE may thus show advantages over MOG-induced EAE., (Copyright © 2020 Faber, Kurtoic, Krishnamoorthy, Weber, Pütz, Müller-Myhsok, Weber and Andlauer.)

Perivascular astrocyte processes (PAP) surround cerebral endothelial cells (ECs) and modulate the strengthening of tight junctions to influence blood-brain barrier (BBB) permeability. Morphologically altered astrocytes may affect barrier properties and trigger the onset of brain pathologies. However, astrocyte-dependent mediators of these events remain poorly studied. Here, we show a pharmacologically driven elevated expression and release of growth/differentiation factor 15 (GDF15) in rat primary astrocytes and cerebral PAP. GDF15 has been shown to possess trophic properties for motor neurons, prompting us to hypothesize similar effects on astrocytes. Indeed, its increased expression and release occurred simultaneously to morphological changes of astrocytes in vitro and PAP, suggesting modulatory effects of GDF15 on these cells, but also neighboring EC. Administration of recombinant GDF15 was sufficient to promote astrocyte remodeling and enhance barrier properties between ECs in vitro, whereas its pharmacogenetic abrogation prevented these effects. We validated our findings in male high anxiety-related behavior rats, an animal model of depressive-like behavior, with shrunk PAP associated with reduced expression of the junctional protein claudin-5, which were both restored by a pharmacologically induced increase in GDF15 expression. Thus, we identified GDF15 as an astrocyte-derived trigger of astrocyte process remodeling linked to enhanced tight junction strengthening at the BBB., (© 2020 Wiley Periodicals, Inc.)

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.

The identification of generalizable treatment response classes (TRC[s]) in major depressive disorder (MDD) would facilitate comparisons across studies and the development of treatment prediction algorithms. Here, we investigated whether such stable TRCs can be identified and predicted by clinical baseline items. We analyzed data from an observational MDD cohort (Munich Antidepressant Response Signature [MARS] study, N = 1017), treated individually by psychopharmacological and psychotherapeutic means, and a multicenter, partially randomized clinical/pharmacogenomic study (Genome-based Therapeutic Drugs for Depression [GENDEP], N = 809). Symptoms were evaluated up to week 16 (or discharge) in MARS and week 12 in GENDEP. Clustering was performed on 809 MARS patients (discovery sample) using a mixed model with the integrated completed likelihood criterion for the assessment of cluster stability, and validated through a distinct MARS validation sample and GENDEP. A random forest algorithm was used to identify prediction patterns based on 50 clinical baseline items. From the clustering of the MARS discovery sample, seven TRCs emerged ranging from fast and complete response (average 4.9 weeks until discharge, 94% remitted patients) to slow and incomplete response (10% remitted patients at week 16). These proved stable representations of treatment response dynamics in both the MARS and the GENDEP validation sample. TRCs were strongly associated with established response markers, particularly the rate of remitted patients at discharge. TRCs were predictable from clinical items, particularly personality items, life events, episode duration, and specific psychopathological features. Prediction accuracy improved significantly when cluster-derived slopes were modelled instead of individual slopes. In conclusion, model-based clustering identified distinct and clinically meaningful treatment response classes in MDD that proved robust with regard to capturing response profiles of differently designed studies. Response classes were predictable from clinical baseline characteristics. Conceptually, model-based clustering is translatable to any outcome measure and could advance the large-scale integration of studies on treatment efficacy or the neurobiology of treatment response.

Emerging evidence emphasizes the strong impact of regulatory genomic elements in neurodevelopmental processes and the complex pathways of brain disorders. The present genome-wide quantitative trait loci analyses explore the cis-regulatory effects of single-nucleotide polymorphisms (SNPs) on DNA methylation (meQTL) and gene expression (eQTL) in 110 human hippocampal biopsies. We identify cis-meQTLs at 14,118 CpG methylation sites and cis-eQTLs for 302 3'-mRNA transcripts of 288 genes. Hippocampal cis-meQTL-CpGs are enriched in flanking regions of active promoters, CpG island shores, binding sites of the transcription factor CTCF and brain eQTLs. Cis-acting SNPs of hippocampal meQTLs and eQTLs significantly overlap schizophrenia-associated SNPs. Correlations of CpG methylation and RNA expression are found for 34 genes. Our comprehensive maps of cis-acting hippocampal meQTLs and eQTLs provide a link between disease-associated SNPs and the regulatory genome that will improve the functional interpretation of non-coding genetic variants in the molecular genetic dissection of brain disorders.

Background: Restless legs syndrome is a prevalent chronic neurological disorder with potentially severe mental and physical health consequences. Clearer understanding of the underlying pathophysiology is needed to improve treatment options. We did a meta-analysis of genome-wide association studies (GWASs) to identify potential molecular targets., Methods: In the discovery stage, we combined three GWAS datasets (EU-RLS GENE, INTERVAL, and 23andMe) with diagnosis data collected from 2003 to 2017, in face-to-face interviews or via questionnaires, and involving 15 126 cases and 95 725 controls of European ancestry. We identified common variants by fixed-effect inverse-variance meta-analysis. Significant genome-wide signals (p≤5 × 10 -8 ) were tested for replication in an independent GWAS of 30 770 cases and 286 913 controls, followed by a joint analysis of the discovery and replication stages. We did gene annotation, pathway, and gene-set-enrichment analyses and studied the genetic correlations between restless legs syndrome and traits of interest., Findings: We identified and replicated 13 new risk loci for restless legs syndrome and confirmed the previously identified six risk loci. MEIS1 was confirmed as the strongest genetic risk factor for restless legs syndrome (odds ratio 1·92, 95% CI 1·85-1·99). Gene prioritisation, enrichment, and genetic correlation analyses showed that identified pathways were related to neurodevelopment and highlighted genes linked to axon guidance (associated with SEMA6D), synapse formation (NTNG1), and neuronal specification (HOXB cluster family and MYT1)., Interpretation: Identification of new candidate genes and associated pathways will inform future functional research. Advances in understanding of the molecular mechanisms that underlie restless legs syndrome could lead to new treatment options. We focused on common variants; thus, additional studies are needed to dissect the roles of rare and structural variations., Funding: Deutsche Forschungsgemeinschaft, Helmholtz Zentrum München-Deutsches Forschungszentrum für Gesundheit und Umwelt, National Research Institutions, NHS Blood and Transplant, National Institute for Health Research, British Heart Foundation, European Commission, European Research Council, National Institutes of Health, National Institute of Neurological Disorders and Stroke, NIH Research Cambridge Biomedical Research Centre, and UK Medical Research Council., (Copyright © 2017 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

The immune system plays a major role in human health and disease, and understanding genetic causes of interindividual variability of immune responses is vital. Here, we isolate monocytes from 134 genotyped individuals, stimulate these cells with three defined microbe-associated molecular patterns (LPS, MDP, and 5'-ppp-dsRNA), and profile the transcriptomes at three time points. Mapping expression quantitative trait loci (eQTL), we identify 417 response eQTLs (reQTLs) with varying effects between conditions. We characterize the dynamics of genetic regulation on early and late immune response and observe an enrichment of reQTLs in distal cis-regulatory elements. In addition, reQTLs are enriched for recent positive selection with an evolutionary trend towards enhanced immune response. Finally, we uncover reQTL effects in multiple GWAS loci and show a stronger enrichment for response than constant eQTLs in GWAS signals of several autoimmune diseases. This demonstrates the importance of infectious stimuli in modifying genetic predisposition to disease.Insight into the genetic influence on the immune response is important for the understanding of interindividual variability in human pathologies. Here, the authors generate transcriptome data from human blood monocytes stimulated with various immune stimuli and provide a time-resolved response eQTL map.

The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (r g =-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness.

Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five previously unknown loci for intracranial volume and confirmed two known signals. Four of the loci were also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height. We found a high genetic correlation with child head circumference (ρ genetic = 0.748), which indicates a similar genetic background and allowed us to identify four additional loci through meta-analysis (N combined = 37,345). Variants for intracranial volume were also related to childhood and adult cognitive function, and Parkinson's disease, and were enriched near genes involved in growth pathways, including PI3K-AKT signaling. These findings identify the biological underpinnings of intracranial volume and their link to physiological and pathological traits.

Background: Fingolimod (FTY720) is the first sphingosine-1-phosphate (S1P) receptor modulator approved for the treatment of multiple sclerosis. The phosphorylated active metabolite FTY720-phosphate (FTY-P) interferes with lymphocyte trafficking. In addition, it accumulates in the CNS and reduces brain atrophy in multiple sclerosis (MS), and neuroprotective effects are hypothesized., Methods: Human primary astrocytes as well as human astrocytoma cells were stimulated with FTY-P or S1P. We analyzed gene expression by a genome-wide microarray and validated induced candidate genes by quantitative PCR (qPCR) and ELISA. To identify the S1P-receptor subtypes involved, we applied a membrane-impermeable S1P analog (dihydro-S1P), receptor subtype specific agonists and antagonists, as well as RNAi silencing., Results: FTY-P induced leukemia inhibitory factor (LIF), interleukin 11 (IL11), and heparin-binding EGF-like growth factor (HBEGF) mRNA, as well as secretion of LIF and IL11 protein. In order to mimic an inflammatory milieu as observed in active MS lesions, we combined FTY-P application with tumor necrosis factor (TNF). In the presence of this key inflammatory cytokine, FTY-P synergistically induced LIF, HBEGF, and IL11 mRNA, as well as secretion of LIF and IL11 protein. TNF itself induced inflammatory, B-cell promoting, and antiviral factors (CXCL10, BAFF, MX1, and OAS2). Their induction was blocked by FTY-P. After continuous exposure of cells to FTY-P or S1P for up to 7 days, the extent of induction of neurotrophic factors and the suppression of TNF-induced inflammatory genes declined but was still detectable. The induction of neurotrophic factors was mediated via surface S1P receptors 1 (S1PR1) and 3 (S1PR3)., Conclusions: We identified effects of FTY-P on astrocytes, namely induction of neurotrophic mediators (LIF, HBEGF, and IL11) and inhibition of TNF-induced inflammatory genes (CXCL10, BAFF, MX1, and OAS2). This supports the view that a part of the effects of fingolimod may be mediated via astrocytes.

Genomic copy number variants (CNVs) have been implicated in multiple psychiatric disorders, but not much is known about their influence on anxiety disorders specifically. Using next-generation sequencing (NGS) and two additional array-based genotyping approaches, we detected CNVs in a mouse model consisting of two inbred mouse lines showing high (HAB) and low (LAB) anxiety-related behavior, respectively. An influence of CNVs on gene expression in the central (CeA) and basolateral (BLA) amygdala, paraventricular nucleus (PVN), and cingulate cortex (Cg) was shown by a two-proportion Z-test (p = 1.6 x 10-31), with a positive correlation in the CeA (p = 0.0062), PVN (p = 0.0046) and Cg (p = 0.0114), indicating a contribution of CNVs to the genetic predisposition to trait anxiety in the specific context of HAB/LAB mice. In order to confirm anxiety-relevant CNVs and corresponding genes in a second mouse model, we further examined CD-1 outbred mice. We revealed the distribution of CNVs by genotyping 64 CD 1 individuals using a high-density genotyping array (Jackson Laboratory). 78 genes within those CNVs were identified to show nominally significant association (48 genes), or a statistical trend in their association (30 genes) with the time animals spent on the open arms of the elevated plus-maze (EPM). Fifteen of them were considered promising candidate genes of anxiety-related behavior as we could show a significant overlap (permutation test, p = 0.0051) with genes within HAB/LAB CNVs. Thus, here we provide what is to our knowledge the first extensive catalogue of CNVs in CD-1 mice and potential corresponding candidate genes linked to anxiety-related behavior in mice.

Analysis of the function of the hypothalamic-pituitary-adrenal (HPA)-axis in patients suffering from posttraumatic stress disorder (PTSD) has hitherto produced inconsistent findings, inter alia in the Trier Social Stress Test (TSST). To address these inconsistencies, we compared a sample of 23 female PTSD patients with either early life trauma (ELT) or adult trauma (AT) or combined ELT and AT to 18 age-matched non-traumatized female healthy controls in the TSST which was preceded by intensive baseline assessments. During the TSST, we determined a variety of clinical, psychological, endocrine and cardiovascular parameters as well as expression levels of four HPA-axis related genes. Using a previously reported definition of HPA-axis responsive versus non-responsive phenotypes, we identified for the first time two clinically and biologically distinct HPA-axis reactivity subgroups of PTSD. One subgroup ("non-responders") showed a blunted HPA-axis response and distinct clinical and biological characteristics such as a higher prevalence of trauma-related dissociative symptoms and of combined AT and ELT as well as alterations in the expression kinetics of the genes encoding for the mineralocorticoid receptor (MR) and for FK506 binding protein 51 (FKBP51). Interestingly, this non-responder subgroup largely drove the relatively diminished HPA axis response of the total cohort of PTSD patients. These findings are limited by the facts that the majority of patients was medicated, by the lack of traumatized controls and by the relatively small sample size. The here for the first time identified and characterized HPA-axis reactivity endophenotypes offer an explanation for the inconsistent reports on HPA-axis function in PTSD and, moreover, suggest that most likely other factors than HPA-axis reactivity play a decisive role in determination of PTSD core symptom severity., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

The highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume and intracranial volume. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10(-33); 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction.

Response to antidepressant treatment is highly variable with some patients responding within a few weeks, whereas others have to wait for months until the onset of clinical effects. Gene expression profiling may be a tool to identify markers of antidepressant treatment response and new potential drug targets. In a first step, we selected 12 male, age- and severity-matched pairs of remitters and nonresponders, and analyzed expression profiles in peripheral blood at admission and after 2 and 5 weeks of treatment using Illumina expression arrays. We identified 127 transcripts significantly associated with treatment response with a minimal P-value of 9.41 × 10(-)(4) (false discovery rate-corrected). Analysis of selected transcripts in an independent replication sample of 142 depressed inpatients confirmed that lower expression of retinoid-related orphan receptor alpha (RORa, P=6.23 × 10(-4)), germinal center expressed transcript 2 (GCET2, P=2.08 × 10(-2)) and chitinase 3-like protein 2 (CHI3L2, P=4.45 × 10(-2)) on admission were associated with beneficial treatment response. In addition, leukocyte-specific protein 1 (LSP1) significantly decreased after 5 weeks of treatment in responders (P=2.91 × 10(-2)). Additional genetic, in vivo stress responsitivity data and murine gene expression findings corroborate our finding of RORa as a transcriptional marker of antidepressant response. In summary, using a genome-wide transcriptomics approach and subsequent validation studies, we identified several transcripts including the circadian gene transcript RORa that may serve as biomarkers indicating antidepressant treatment response.

Toll-like receptors (TLRs) play a key role in innate immunity. Apart from their function in host defense, dysregulation in TLR signalling can confer risk to autoimmune diseases, septic shock or cancer. Here we report genetic variants and transcripts that are active only during TLR signalling and contribute to interindividual differences in immune response. Comparing unstimulated versus TLR4-stimulated monocytes reveals 1,471 expression quantitative trait loci (eQTLs) that are unique to TLR4 stimulation. Among these we find functional SNPs for the expression of NEU4, CCL14, CBX3 and IRF5 on TLR4 activation. Furthermore, we show that SNPs conferring risk to primary biliary cirrhosis (PBC), inflammatory bowel disease (IBD) and celiac disease are immune response eQTLs for PDGFB and IL18R1. Thus, PDGFB and IL18R1 represent plausible candidates for studying the pathophysiology of these disorders in the context of TLR4 activation. In summary, this study presents novel insights into the genetic basis of the innate immune response and exemplifies the value of eQTL studies in the context of exogenous cell stimulation.

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.

Leptin, a peptide hormone from adipose tissue and key player in weight regulation, has been suggested to be involved in sleep and cognition and to exert antidepressant-like effects, presumably via its action on the HPA-axis and hippocampal function. This led us to investigate whether genetic variants in the leptin gene, the level of leptin mRNA-expression and leptin serum concentrations are associated with response to antidepressant treatment. Our sample consisted of inpatients from the Munich Antidepressant Response Signature (MARS) project with weekly Hamilton Depression ratings, divided into two subsamples. In the exploratory sample (n=251) 17 single nucleotide polymorphisms (SNPs) covering the leptin gene region were genotyped. We found significant associations of several SNPs with impaired antidepressant treatment outcome and impaired cognitive performance after correction for multiple testing. The SNP (rs10487506) showing the highest association with treatment response (p=3.9×10(-5)) was analyzed in the replication sample (n=358) and the association could be verified (p=0.021) with response to tricyclic antidepressants. In an additional meta-analysis combining results from the MARS study with data from the Genome-based Therapeutic Drugs for Depression (GENDEP) and the Sequenced Treatment Alternatives to Relieve Depression (STAR(⁎)D) studies, nominal associations of several polymorphisms in the upstream vicinity of rs10487506 with treatment outcome were detected (p=0.001). In addition, we determined leptin mRNA expression in lymphocytes and leptin serum levels in subsamples of the MARS study. Unfavorable treatment outcome was accompanied with decreased leptin mRNA and leptin serum levels. Our results suggest an involvement of leptin in antidepressant action and cognitive function in depression with genetic polymorphisms in the leptin gene, decreased leptin gene expression and leptin deficiency in serum being risk factors for resistance to antidepressant therapy in depressed patients., (Copyright © 2012 Elsevier B.V. and ECNP. All rights reserved.)

Most of the commonly used antidepressants block monoamine reuptake transporters to enhance serotonergic or noradrenergic neurotransmission. Effects besides or downstream of monoamine reuptake inhibition are poorly understood and yet presumably important for the drugs' mode of action. In the present study we aimed at identifying hippocampal cellular pathway alterations in DBA/2 mice using paroxetine as a representative Selective Serotonin Reuptake Inhibitor (SSRI). Furthermore we identified biomarker candidates for the assessment of antidepressant treatment effects in plasma. Hippocampal protein levels were compared between chronic paroxetine- and vehicle-treated animals using in vivo(15)N metabolic labeling combined with mass spectrometry. We also studied the time course of metabolite level changes in hippocampus and plasma using a targeted polar metabolomics profiling platform. In silico pathway analyses revealed profound alterations related to hippocampal energy metabolism. Glycolytic metabolite levels acutely increased while Krebs cycle metabolite levels decreased upon chronic treatment. Changes in energy metabolism were influenced by altered glycogen metabolism rather than by altered glycolytic or Krebs cycle enzyme levels. Increased energy levels were reflected by an increased ATP/ADP ratio and by increased ratios of high-to-low energy purines and pyrimidines. In the course of our analyses we also identified myo-inositol as a biomarker candidate for the assessment of antidepressant treatment effects in the periphery. This study defines the cellular response to paroxetine treatment at the proteome and metabolome levels in the hippocampus of DBA/2 mice and suggests novel SSRI modes of action that warrant consideration in antidepressant development efforts., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Background: Until recently, genotype studies were limited to the investigation of single SNP effects due to the computational burden incurred when studying pairwise interactions of SNPs. However, some genetic effects as simple as coloring (in plants and animals) cannot be ascribed to a single locus but only understood when epistasis is taken into account [1]. It is expected that such effects are also found in complex diseases where many genes contribute to the clinical outcome of affected individuals. Only recently have such problems become feasible computationally., Objectives: The inherently parallel structure of the problem makes it a perfect candidate for massive parallelization on either grid or cloud architectures. Since we are also dealing with confidential patient data, we were not able to consider a cloud-based solution but had to find a way to process the data in-house and aimed to build a local GPU-based grid structure., Methods: Sequential epistatsis calculations were ported to GPU using CUDA at various levels. Parallelization on the CPU was compared to corresponding GPU counterparts with regards to performance and cost., Results: A cost-effective solution was created by combining custom-built nodes equipped with relatively inexpensive consumer-level graphics cards with highly parallel GPUs in a local grid. The GPU method outperforms current cluster-based systems on a price/performance criterion, as a single GPU shows speed performance comparable up to 200 CPU cores., Conclusion: The outlined approach will work for problems that easily lend themselves to massive parallelization. Code for various tasks has been made available and ongoing development of tools will further ease the transition from sequential to parallel algorithms.

Background: The hypothalamic-pituitary-adrenal (HPA) axis is essential to control physiological stress responses in mammals. Its dysfunction is related to several mental disorders, including anxiety and depression. The aim of this study was to identify genetic loci underlying the endocrine regulation of the HPA axis., Method: High (HAB) and low (LAB) anxiety-related behaviour mice were established by selective inbreeding of outbred CD-1 mice to model extremes in trait anxiety. Additionally, HAB vs. LAB mice exhibit comorbid characteristics including a differential corticosterone response upon stress exposure. We crossbred HAB and LAB lines to create F1 and F2 offspring. To identify the contribution of the endocrine phenotypes to the total phenotypic variance, we examined multiple behavioural paradigms together with corticosterone secretion-based phenotypes in F2 mice by principal component analysis. Further, to pinpoint the genomic loci of the quantitative trait of the HPA axis stress response, we conducted genome-wide multipoint oligogenic linkage analyses based on Bayesian Markov chain Monte Carlo approach as well as parametric linkage in three-generation pedigrees, followed by a two-dimensional scan for epistasis and association analysis in freely segregating F2 mice using 267 single-nucleotide polymorphisms (SNPs), which were identified to consistently differ between HAB and LAB mice as genetic markers., Results: HPA axis reactivity measurements and behavioural phenotypes were represented by independent principal components and demonstrated no correlation. Based on this finding, we identified one single quantitative trait locus (QTL) on chromosome 3 showing a very strong evidence for linkage (2ln (L-score) > 10, LOD > 23) and significant association (lowest Bonferroni adjusted p < 10-28) to the neuroendocrine stress response. The location of the linkage peak was estimated at 42.3 cM (95% confidence interval: 41.3 - 43.3 cM) and was shown to be in epistasis (p-adjusted < 0.004) with the locus at 35.3 cM on the same chromosome. The QTL harbours genes involved in steroid synthesis and cardiovascular effects., Conclusion: The very prominent effect on stress-induced corticosterone secretion of the genomic locus on chromosome 3 and its involvement in epistasis highlights the critical role of this specific locus in the regulation of the HPA axis.

Although gene expression profiles in peripheral blood in major depression are not likely to identify genes directly involved in the pathomechanism of affective disorders, they may serve as biomarkers for this disorder. As previous studies using baseline gene expression profiles have provided mixed results, our approach was to use an in vivo dexamethasone challenge test and to compare glucocorticoid receptor (GR)-mediated changes in gene expression between depressed patients and healthy controls. Whole genome gene expression data (baseline and following GR-stimulation with 1.5 mg dexamethasone p.o.) from two independent cohorts were analyzed to identify gene expression pattern that would predict case and control status using a training (N=18 cases/18 controls) and a test cohort (N=11/13). Dexamethasone led to reproducible regulation of 2670 genes in controls and 1151 transcripts in cases. Several genes, including FKBP5 and DUSP1, previously associated with the pathophysiology of major depression, were found to be reliable markers of GR-activation. Using random forest analyses for classification, GR-stimulated gene expression outperformed baseline gene expression as a classifier for case and control status with a correct classification of 79.1 vs 41.6% in the test cohort. GR-stimulated gene expression performed best in dexamethasone non-suppressor patients (88.7% correctly classified with 100% sensitivity), but also correctly classified 77.3% of the suppressor patients (76.7% sensitivity), when using a refined set of 19 genes. Our study suggests that in vivo stimulated gene expression in peripheral blood cells could be a promising molecular marker of altered GR-functioning, an important component of the underlying pathology, in patients suffering from depressive episodes.

Identifying genetic variants influencing human brain structures may reveal new biological mechanisms underlying cognition and neuropsychiatric illness. The volume of the hippocampus is a biomarker of incipient Alzheimer's disease and is reduced in schizophrenia, major depression and mesial temporal lobe epilepsy. Whereas many brain imaging phenotypes are highly heritable, identifying and replicating genetic influences has been difficult, as small effects and the high costs of magnetic resonance imaging (MRI) have led to underpowered studies. Here we report genome-wide association meta-analyses and replication for mean bilateral hippocampal, total brain and intracranial volumes from a large multinational consortium. The intergenic variant rs7294919 was associated with hippocampal volume (12q24.22; N = 21,151; P = 6.70 × 10(-16)) and the expression levels of the positional candidate gene TESC in brain tissue. Additionally, rs10784502, located within HMGA2, was associated with intracranial volume (12q14.3; N = 15,782; P = 1.12 × 10(-12)). We also identified a suggestive association with total brain volume at rs10494373 within DDR2 (1q23.3; N = 6,500; P = 5.81 × 10(-7)).

Due to recent advances in genotyping technologies, mapping phenotypes to single loci in the genome has become a standard technique in statistical genetics. However, one-locus mapping fails to explain much of the phenotypic variance in complex traits. Here, we present GLIDE, which maps phenotypes to pairs of genetic loci and systematically searches for the epistatic interactions expected to reveal part of this missing heritability. GLIDE makes use of the computational power of consumer-grade graphics cards to detect such interactions via linear regression. This enabled us to conduct a systematic two-locus mapping study on seven disease data sets from the Wellcome Trust Case Control Consortium and on in-house hippocampal volume data in 6 h per data set, while current single CPU-based approaches require more than a year's time to complete the same task., (Copyright © 2012 S. Karger AG, Basel.)

MAP kinase signaling has been implicated in brain development, long-term memory, and the response to antidepressants. Inducible Braf knockout mice, which exhibit protein depletion in principle forebrain neurons, enabled us to unravel a new role of neuronal MAPK signaling for emotional behavior. Braf mice that were induced during adulthood showed normal anxiety but increased depression-like behavior, in accordance with pharmacological findings. In contrast, the inducible or constitutive inactivation of Braf in the juvenile brain leads to normal depression-like behavior but decreased anxiety in adults. In juvenile, constitutive mutants we found no alteration of GABAergic neurotransmission but reduced neuronal arborization in the dentate gyrus. Analysis of gene expression in the hippocampus revealed nine downregulated MAPK target genes that represent candidates to cause the mutant phenotype.Our results reveal the differential function of MAPK signaling in juvenile and adult life phases and emphasize the early postnatal period as critical for the determination of anxiety in adults. Moreover, these results validate inducible gene inactivation as a new valuable approach, allowing it to discriminate between gene function in the adult and the developing postnatal brain.

In 2008, van den Oord et al. identified in a genome-wide association study the MAM domain containing glycosylphosphatidylinositol anchor 2 gene (MDGA2 or MAMDC1) as a new candidate for neuroticism. In addition to the replication attempt of this association, we further investigated the role of MDGA2 with respect to harm avoidance (HA), a personality trait highly related to neuroticism. In a sample of mentally healthy volunteers (n=541) and depressed patients (n=199), neuroticism and HA were assessed with Eysenck's Revised Personality Questionnaire and Cloninger's Tridimensional Personality Questionnaire. Genotypic information (Illumina Bead Chip HumanHap300) of 100 single nucleotide polymorphisms (SNPs) located in the MDGA2 gene (±5 kb) was available, and additional four SNPs for replication were imputed. We were able to replicate the association between MDGA2 and neuroticism for the strongest SNPs of the genome-wide association study. It could further be shown that volunteers homozygous for the T-allele of SNP rs2416054 showed higher scores in the HA4 subscale 'Fatigability and asthenia' (Pnominal=0.0006), remaining significant after correction for multiple testing (Pwy-corrected=0.045). The same SNP also showed an association with HA4 in the patients' sample (Pnominal=0.03). Our finding provides further support for a link between variants in the MDGA2 gene and specific neuroticism-related phenotypes.

Context: Polymorphisms in the gene encoding the glucocorticoid receptor (GR) regulating co-chaperone FKBP5 have been shown to alter GR sensitivity and are associated with an increased risk to develop posttraumatic stress disorder (PTSD)., Objective: To investigate interactions of the FKBP5 single-nucleotide polymorphism rs9296158 and PTSD symptoms on baseline cortisol level, low-dose dexamethasone suppression, and whole-blood gene expression., Design: Association of FKBP5 genotypes and PTSD symptoms with endocrine measures and genome-wide expression profiles., Setting: Waiting rooms of general medical and gynecological clinics of an urban hospital at Emory University., Participants: The 211 participants were primarily African American (90.05%) and of low socioeconomic status and had high rates of trauma and PTSD., Main Outcome Measures: Baseline and post-dexamethasone suppression cortisol measures and gene expression levels., Results: In our endocrine study, we found that only risk allele A carriers of rs9296158 showed GR supersensitivity with PTSD; in contrast, baseline cortisol levels were decreased in PTSD only in patients with the GG genotype. Expression of 183 transcripts was significantly correlated with PTSD symptoms after multiple testing corrections. When adding FKBP5 genotype and its interaction with PTSD symptoms, expression levels of an additional 32 genes were significantly regulated by the interaction term. Within these 32 genes, previously reported PTSD candidates were identified, including FKBP5 and the IL18 and STAT pathways. Significant overrepresentation of steroid hormone transcription factor binding sites within these 32 transcripts was observed, highlighting the fact that the earlier-described genotype and PTSD-dependent differences in GR sensitivity could drive the observed gene expression pattern. Results were validated by reverse transcriptase-polymerase chain reaction and replicated in an independent sample (N = 98)., Conclusions: These data suggest that the inheritance of GR sensitivity-moderating FKBP5 polymorphisms can determine specific types of hypothalamic-pituitary-adrenal axis dysfunction within PTSD, which are also reflected in gene-expression changes of a subset of GR-responsive genes. Thus, these findings indicate that functional variants in FKBP5 are associated with biologically distinct subtypes of PTSD.

Motivation: In recent years, numerous genome-wide association studies have been conducted to identify genetic makeup that explains phenotypic differences observed in human population. Analytical tests on single loci are readily available and embedded in common genome analysis software toolset. The search for significant epistasis (gene-gene interactions) still poses as a computational challenge for modern day computing systems, due to the large number of hypotheses that have to be tested., Results: In this article, we present an approach to epistasis detection by exhaustive testing of all possible SNP pairs. The search strategy based on the Hilbert-Schmidt Independence Criterion can help delineate various forms of statistical dependence between the genetic markers and the phenotype. The actual implementation of this search is done on the highly parallelized architecture available on graphics processing units rendering the completion of the full search feasible within a day., Availability: The program is available at http://www.mpipsykl.mpg.de/epigpuhsic/., Contact: tony@mpipsykl.mpg.de.

The lifetime prevalence of panic disorder (PD) is up to 4% worldwide and there is substantial evidence that genetic factors contribute to the development of PD. Single-nucleotide polymorphisms (SNPs) in TMEM132D, identified in a whole-genome association study (GWAS), were found to be associated with PD in three independent samples, with a two-SNP haplotype associated in each of three samples in the same direction, and with a P-value of 1.2e-7 in the combined sample (909 cases and 915 controls). Independent SNPs in this gene were also associated with the severity of anxiety symptoms in patients affected by PD or panic attacks as well as in patients suffering from unipolar depression. Risk genotypes for PD were associated with higher TMEM132D mRNA expression levels in the frontal cortex. In parallel, using a mouse model of extremes in trait anxiety, we could further show that anxiety-related behavior was positively correlated with Tmem132d mRNA expression in the anterior cingulate cortex, central to the processing of anxiety/fear-related stimuli, and that in this animal model a Tmem132d SNP is associated with anxiety-related behavior in an F2 panel. TMEM132D may thus be an important new candidate gene for PD as well as more generally for anxiety-related behavior.

Detection of epistatic interaction between loci has been postulated to provide a more in-depth understanding of the complex biological and biochemical pathways underlying human diseases. Studying the interaction between two loci is the natural progression following traditional and well-established single locus analysis. However, the added costs and time duration required for the computation involved have thus far deterred researchers from pursuing a genome-wide analysis of epistasis. In this paper, we propose a method allowing such analysis to be conducted very rapidly. The method, dubbed EPIBLASTER, is applicable to case-control studies and consists of a two-step process in which the difference in Pearson's correlation coefficients is computed between controls and cases across all possible SNP pairs as an indication of significant interaction warranting further analysis. For the subset of interactions deemed potentially significant, a second-stage analysis is performed using the likelihood ratio test from the logistic regression to obtain the P-value for the estimated coefficients of the individual effects and the interaction term. The algorithm is implemented using the parallel computational capability of commercially available graphical processing units to greatly reduce the computation time involved. In the current setup and example data sets (211 cases, 222 controls, 299468 SNPs; and 601 cases, 825 controls, 291095 SNPs), this coefficient evaluation stage can be completed in roughly 1 day. Our method allows for exhaustive and rapid detection of significant SNP pair interactions without imposing significant marginal effects of the single loci involved in the pair.

Behavioral endophenotypes are determined by a multitude of counteracting but precisely balanced molecular and physiological mechanisms. In this study, we aim to identify potential novel molecular targets that contribute to the multigenic trait "anxiety". We used microarrays to investigate the gene expression profiles of different brain regions within the limbic system of mice which were selectively bred for either high (HAB) or low (LAB) anxiety-related behavior, and also show signs of comorbid depression-like behavior. We identified and confirmed sex-independent differences in the basal expression of 13 candidate genes, using tissue from the entire brain, including coronin 7 (Coro7), cathepsin B (Ctsb), muscleblind-like 1 (Mbnl1), metallothionein 1 (Mt1), solute carrier family 25 member 17 (Slc25a17), tribbles homolog 2 (Trib2), zinc finger protein 672 (Zfp672), syntaxin 3 (Stx3), ATP-binding cassette, sub-family A member 2 (Abca2), ectonucleotide pyrophosphatase/phosphodiesterase 5 (Enpp5), high mobility group nucleosomal binding domain 3 (Hmgn3) and pyruvate dehydrogenase beta (Pdhb). Additionally, we confirmed brain region-specific differences in the expression of synaptotagmin 4 (Syt4).Our identification of about 90 polymorphisms in Ctsb suggested that this gene might play a critical role in shaping our mouse model's behavioral endophenotypes. Indeed, the assessment of anxiety-related and depression-like behaviors of Ctsb knock-out mice revealed an increase in depression-like behavior in females. Altogether, our results suggest that Ctsb has significant effects on emotionality, irrespective of the tested mouse strain, making it a promising target for future pharmacotherapy.

Background: Dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis is a hallmark of complex and multifactorial psychiatric diseases such as anxiety and mood disorders. About 50-60% of patients with major depression show HPA axis dysfunction, i.e. hyperactivity and impaired negative feedback regulation. The neuropeptide corticotropin-releasing hormone (CRH) and its receptor type 1 (CRHR1) are key regulators of this neuroendocrine stress axis. Therefore, we analyzed CRH/CRHR1-dependent gene expression data obtained from the pituitary corticotrope cell line AtT-20, a well-established in vitro model for CRHR1-mediated signal transduction. To extract significantly regulated genes from a genome-wide microarray data set and to deduce underlying CRHR1-dependent signaling networks, we combined supervised and unsupervised algorithms., Results: We present an efficient variable selection strategy by consecutively applying univariate as well as multivariate methods followed by graphical models. First, feature preselection was used to exclude genes not differentially regulated over time from the dataset. For multivariate variable selection a maximum likelihood (MLHD) discriminant function within GALGO, an R package based on a genetic algorithm (GA), was chosen. The topmost genes representing major nodes in the expression network were ranked to find highly separating candidate genes. By using groups of five genes (chromosome size) in the discriminant function and repeating the genetic algorithm separately four times we found eleven genes occurring at least in three of the top ranked result lists of the four repetitions. In addition, we compared the results of GA/MLHD with the alternative optimization algorithms greedy selection and simulated annealing as well as with the state-of-the-art method random forest. In every case we obtained a clear overlap of the selected genes independently confirming the results of MLHD in combination with a genetic algorithm. With two unsupervised algorithms, principal component analysis and graphical Gaussian models, putative interactions of the candidate genes were determined and reconstructed by literature mining. Differential regulation of six candidate genes was validated by qRT-PCR., Conclusions: The combination of supervised and unsupervised algorithms in this study allowed extracting a small subset of meaningful candidate genes from the genome-wide expression data set. Thereby, variable selection using different optimization algorithms based on linear classifiers as well as the nonlinear random forest method resulted in congruent candidate genes. The calculated interacting network connecting these new target genes was bioinformatically mapped to known CRHR1-dependent signaling pathways. Additionally, the differential expression of the identified target genes was confirmed experimentally.

Background: The pivotal role of stress in the precipitation of psychiatric diseases such as depression is generally accepted. This study aims at the identification of genes that are directly or indirectly responding to stress. Inbred mouse strains that had been evidenced to differ in their stress response as well as in their response to antidepressant treatment were chosen for RNA profiling after stress exposure. Gene expression and regulation was determined by microarray analyses and further evaluated by bioinformatics tools including pathway and cluster analyses., Results: Forced swimming as acute stressor was applied to C57BL/6J and DBA/2J mice and resulted in sets of regulated genes in the paraventricular nucleus of the hypothalamus (PVN), 4 h or 8 h after stress. Although the expression changes between the mouse strains were quite different, they unfolded in phases over time in both strains. Our search for connections between the regulated genes resulted in potential novel signalling pathways in stress. In particular, Guanine nucleotide binding protein, alpha inhibiting 2 (GNAi2) and amyloid β (A4) precursor protein (APP) were detected as stress-regulated genes, and together with other genes, seem to be integrated into stress-responsive pathways and gene networks in the PVN., Conclusions: This search for stress-regulated genes in the PVN revealed its impact on interesting genes (GNAi2 and APP) and a novel gene network. In particular the expression of APP in the PVN that is governing stress hormone balance, is of great interest. The reported neuroprotective role of this molecule in the CNS supports the idea that a short acute stress can elicit positive adaptational effects in the brain.

Genes involved in serotonergic and dopaminergic neurotransmission have been hypothesized to affect different aspects of personality, but findings from genetic association studies did not provide conclusive results so far. In previous studies, however, only one or a few polymorphisms within single genes were investigated neglecting the possibility that the genetic associations might be more complex comprising several genes or gene regions. To overcome this limitation, we performed an extended genetic association study analyzing 17 serotonergic (SLC6A4, HTR1A, HTR1B, HTR2A, HTR2C, HTR3A, HTR6, MAOA, TPH1, TPH2) and dopaminergic genes (SLC6A3, DRD2, DRD3, DRD4, COMT, MAOA, TH, DBH), which have been previously reported to be implicated with personality traits. One hundred and ninety-five single nucleotide polymorphisms (SNPs) within these genes were genotyped with the Illumina BeadChip technology (HumanHap300, Human-1) in a sample of 366 mentally healthy Caucasians. Additionally, we tried to replicate our results in an independent sample of further 335 Caucasians. Personality traits in both samples were assessed with the German version of Cloninger's Tridimensional Personality Questionnaire. From 30 SNPs showing associations at a nominal level of significance, two intronic SNPs, rs2770296 and rs927544, both located in the HTR2A gene, withstood correction for multiple testing. These SNPs were associated with the personality trait novelty seeking. The effect of rs927544 could be replicated for the novelty seeking subscale extravagance, and the same SNP was also associated with extravagance in the combined samples. Our results show that HTR2A polymorphisms modulate facets of novelty seeking behaviour in healthy adults suggesting that serotonergic neurotransmission is involved in this phenotype.

The postnatal development of the mouse is characterized by a stress hypo-responsive period (SHRP), where basal corticosterone levels are low and responsiveness to mild stressors is reduced. Maternal separation is able to disrupt the SHRP and is widely used to model early trauma. In this study we aimed at identifying of brain systems involved in acute and possible long-term effects of maternal separation. We conducted a microarray-based gene expression analysis in the hypothalamic paraventricular nucleus after maternal separation, which revealed 52 differentially regulated genes compared to undisturbed controls, among them are 37 up-regulated and 15 down-regulated genes. One of the prominently up-regulated genes, angiotensinogen, was validated using in-situ hybridization. Angiotensinogen is the precursor of angiotensin II, the main effector of the brain renin-angiotensin system (RAS), which is known to be involved in stress system modulation in adult animals. Using the selective angiotensin type I receptor [AT(1)] antagonist candesartan we found strong effects on CRH and GR mRNA expression in the brain and ACTH release following maternal separation. AT(1) receptor blockade appears to enhance central effects of maternal separation in the neonate, suggesting a suppressing function of brain RAS during the SHRP. Taken together, our results illustrate the molecular adaptations that occur in the paraventricular nucleus following maternal separation and contribute to identifying signaling cascades that control stress system activity in the neonate.

The QT interval, a measure of cardiac repolarization, predisposes to ventricular arrhythmias and sudden cardiac death (SCD) when prolonged or shortened. A common variant in NOS1AP is known to influence repolarization. We analyze genome-wide data from five population-based cohorts (ARIC, KORA, SardiNIA, GenNOVA and HNR) with a total of 15,842 individuals of European ancestry, to confirm the NOS1AP association and identify nine additional loci at P < 5 x 10(-8). Four loci map near the monogenic long-QT syndrome genes KCNQ1, KCNH2, SCN5A and KCNJ2. Two other loci include ATP1B1 and PLN, genes with established electrophysiological function, whereas three map to RNF207, near LITAF and within NDRG4-GINS3-SETD6-CNOT1, respectively, all of which have not previously been implicated in cardiac electrophysiology. These results, together with an accompanying paper from the QTGEN consortium, identify new candidate genes for ventricular arrhythmias and SCD.

Background: To investigate neurobiological correlates of trait anxiety, CD1 mice were selectively bred for extremes in anxiety-related behavior, with high (HAB) and low (LAB) anxiety-related behavior mice additionally differing in behavioral tests reflecting depression-like behavior., Methodology/ Principal Findings: In this study, microarray analysis, in situ hybridization, quantitative real-time PCR and immunohistochemistry revealed decreased expression of the vasopressin gene (Avp) in the hypothalamic paraventricular (PVN) and supraoptic (SON) nuclei of adult LAB mice compared to HAB, NAB (normal anxiety-related behavior) and HABxLAB F1 intercross controls, without detecting differences in receptor expression or density. By sequencing the regions 2.5 kbp up- and downstream of the Avp gene locus, we could identify several polymorphic loci, differing between the HAB and LAB lines. In the gene promoter, a deletion of twelve bp Delta(-2180-2191) is particularly likely to contribute to the reduced Avp expression detected in LAB animals under basal conditions. Indeed, allele-specific transcription analysis of F1 animals revealed a hypomorphic LAB-specific Avp allele with a reduced transcription rate by 75% compared to the HAB-specific allele, thus explaining line-specific Avp expression profiles and phenotypic features. Accordingly, intra-PVN Avp mRNA levels were found to correlate with anxiety-related and depression-like behaviors. In addition to this correlative evidence, a significant, though moderate, genotype/phenotype association was demonstrated in 258 male mice of a freely-segregating F2 panel, suggesting a causal contribution of the Avp promoter deletion to anxiety-related behavior., Discussion: Thus, the identification of polymorphisms in the Avp gene promoter explains gene expression differences in association with the observed phenotype, thus further strengthening the concept of the critical involvement of centrally released AVP in trait anxiety.

Introduction: Monoamine-based antidepressants inhibit neurotransmitter reuptake within short time. However, it commonly takes several weeks until clinical symptoms start to resolve--indicating the involvement of effects distant from reuptake inhibition., Objective: To unravel other mechanisms involved in drug action, a "reverse" pharmacological approach was applied to determine antidepressant-induced alterations of hippocampal gene expression., Materials and Methods: The behavioral response to long-term paroxetine administration of male DBA/2Ola mice was assessed by the forced swim test (FST), the modified hole board (mHB), and the dark/light box. Hippocampi of test-naive mice were dissected, and changes in gene expression by paroxetine treatment were investigated by means of microarray technology., Results and Discussion: Robust effects of paroxetine on passive stress-coping behavior in the FST were observed. Furthermore, anxiolytic properties of long-term antidepressant treatment could be identified in DBA mice in both, the mHB and dark/light box. Analysis of microarray results revealed a list of 60 genes differentially regulated by chronic paroxetine treatment. Preproenkephalin 1 and inhibin beta-A showed the highest level of transcriptional change. Furthermore, a number of candidates involved in neuroplasticity/neurogenesis emerged (e.g., Bdnf, Gfap, Vim, Sox11, Egr1, Stat3). Seven selected candidates were confirmed by in situ hybridization. Additional immunofluorescence colocalization studies of GFAP and vimentin showed more positive cells to be detected in long-term paroxetine-treated DBA mice., Conclusion: Candidate genes identified in the current study using a mouse strain validated for its responsiveness to long-term paroxetine treatment add, in our opinion, to unraveling the mechanism of action of paroxetine as a representative for SSRIs.

Stress exposure can lead to the precipitation of psychiatric disorders in susceptible individuals, but the molecular underpinnings are incompletely understood. We used forced swimming in mice to reveal stress-regulated genes in the CA3 area of the hippocampus. To determine changes in the transcriptional profile 4 h and 8 h after stress exposure microarrays were used in the two mouse strains C57BL/6J and DBA/2J, which are known for their differential stress response. We discovered a surprisingly distinct set of regulated genes for each strain and followed selected ones by in situ hybridisation. Our results support the concept of a phased transcriptional reaction to stress. Moreover, we suggest novel stress-elicited pathways, which comprise a number of genes involved in the regulation of neuronal plasticity. Furthermore, we focused in particular on dihydropyrimidinase like 2, to which we provide evidence for its regulation by NeuroD, an important factor for neuronal activity-dependent dendritic morphogenesis.

Sixty percent of the patients with restless legs syndrome (RLS) report a positive family history. To date five loci have been mapped on chromosome 12q, 14q, 9p, 2q, and 20p (RLS1-5) but no gene has been identified so far. To identify genes related to RLS, we performed a three-stage association study (explorative study, replication study, high-density mapping) in two Caucasian RLS case-control samples of altogether 918 independent cases and controls. In the explorative study (367 cases and controls, respectively), we screened 1536 SNPs in 366 genes in a 21 Mb region encompassing the RLS1 critical region on chromosome 12. Armitage trend test revealed three genomic regions that were significant (P < 0.05). In the replication study (551 cases and controls, respectively) we genotyped the most significant SNPs of Stage 1. After correction for multiple testing, association was observed with SNP rs7977109 (P(nominal) = 0.00175, P(Westfall-Young) = 0.04895, OR = 0.76228, 95% CI = 0.64310-0.90355), which is in the neuronal nitric oxide synthase (NOS1) gene. High-density mapping using altogether 34 tagging and coding SNPs of the NOS1 gene in both case-control samples further confirmed the significant association results to NOS1. Ten more SNPs revealed significance with nominal P-values from 0.0001 to 0.0482 (genotypic test and Armitage test). Altogether, this study provides evidence for an association of variants in the NOS1 gene and RLS, and suggests the involvement of the NO/arginine pathway in the pathogenesis of RLS. Potential usage of NO modulating agents as new treatment options for RLS have become a challenging aspect for future research of this disorder., (2007 Movement Disorder Society)