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Djurovic, S.

Publications and source records attributed to Djurovic, S..

At least 19 recordsLinked to original sources

Integrative multiomics profiling of cortical brain organoids reveals a druggable alternative splicing program in schizophrenia

Clozapine (CLZ) is the only available pharmacological option for treatment resistant schizophrenia (TRS), but its use is limited due to adverse drug reactions and potential cytotoxicity. Despite decades of research, the precise mechanisms of action of CLZ in the human brain remain poorly understood. To address this, we derived cortical brain organoids from a large cohort of schizophrenia (SCZ) patients and healthy controls and employed a comprehensive multiomics strategy to dissect the cellular mechanisms of long-term CLZ exposure of up to 24 weeks. We uncovered a SCZ-specific and metabolism-independent alternative splicing program that was amenable to non-toxic CLZ treatment. In-depth analysis revealed a key role of exon skipping and intron retention in glutamatergic neurons. This program was further found to recapitulate disease mechanisms in primary human brain tissue and capture splicing-mediated genetic signals of SCZ risk. These findings highlight alternative splicing as a promising avenue for therapeutic developments in TRS.

neuroscience↗

The non-classic psychedelic muscimol suppresses inflammatory signaling and promotes neuroplasticity in schizophrenia-derived human cortical spheroids and astroglia

Schizophrenia (SCZ) is increasingly linked to neuroimmune dysregulation and impaired synaptic plasticity, yet the cellular mechanisms connecting inflammatory signaling to neural dysfunction remain poorly understood. Using human induced pluripotent stem cell (iPSC)-derived cortical spheroids (hCS) and astrocytes from patients with SCZ and matched controls, we investigated the effects of GABAA receptor modulation on immune signaling and neuroplasticity. Inflammatory stimulation induced robust interferon-responsive transcriptional programs, prominently involving the antiviral effector MX1 and related interferon-stimulated genes. Computational deconvolution and cell type-specific analyses identified astrocytes as key mediators of these responses. Muscimol, a non-classic psychedelic and GABAA receptor agonist, suppressed inflammatory gene expression, reduced secretion of proinflammatory cytokines, and attenuated interferon-associated signaling. In addition, muscimol induced neuroplasticity-associated transcriptional programs, including upregulation of NTRK2 and ELK1 in hCSs, and restored impaired glutamate uptake in iPSC-derived SCZ astrocytes. These effects were blocked by GABAA receptor inhibition, confirming receptor-dependent mechanisms. Proteomic analyses of hCS cultures, and independent human dorsolateral prefrontal cortex datasets revealed baseline dysregulation of GABAergic and neurotrophin signaling in SCZ, supporting translational relevance. Together, these findings demonstrate that GABAA receptor activation by muscimol suppresses inflammatory signaling while promoting neuroplasticity in hCSs, and identify astrocytes as central regulators of interferon-dependent neuroimmune dysfunction in SCZ. These results establish non-classic psychedelic compounds as potential modulators of neuroimmune-plasticity coupling and suggest that targeting astrocyte GABAergic signaling may represent a therapeutic strategy for restoring neural homeostasis in SCZ.

neuroscience↗

Beyond Exons: Linking Noncoding Heritability and Polygenicity across Complex Human Traits and Disorders

The genetic architecture of complex traits spans a continuum of polygenicity, yet it remains unclear how differences in polygenicity relate to the functional localization of SNP heritability across the genome. We use a MiXeR-based framework to partition heritability across exonic, intronic, and intergenic regions for 34 traits and introduce a likelihood-based annotation contribution score that quantifies annotation-specific impact on heritability. Exons explain a minority of heritability, and their contribution decreases with increasing polygenicity, from an average of 22% in less polygenic somatic diseases and biomarkers to 13% in highly polygenic psychiatric and cognitive phenotypes. Intergenic fractions show the opposite trend, whereas intronic fractions remain relatively stable. Analysis of a broader set of functional annotations reveals systematic differences along the polygenicity axis: highly polygenic traits show stronger contributions from comparative genomics and variant-effect scores, whereas less polygenic traits show stronger contributions in promoter, transcription, and chromatin annotations. Together, these results indicate that the functional partitioning of heritability systematically varies with polygenicity, pointing to a shift from gene-proximal regulatory architectures to architectures shaped by numerous dispersed regulatory effects as a key determinant of differences in polygenicity across traits.

genetics↗

Computational modelling of novelty detection in the mismatch negativity protocols and its impairments in schizophrenia

The human auditory system rapidly distinguishes between novel and familiar sounds, a process reflected in mismatch negativity (MMN), an EEG-based biomarker of auditory novelty detection. MMN is impaired in psychiatric conditions, most notably schizophrenia (SCZ), yet the neuronal mechanisms underlying this deficit remain unclear. Here, we combined computational modelling and genetic analyses to investigate how SCZ-associated cellular abnormalities affect auditory novelty detection. We developed an integrate-and-fire spiking network model capable of detecting four types of auditory novelty, including stimulus omission. Based on assumptions of short-term depressing synapses between the subpopulations of the network and the existence of neuronal inputs that are phase-locked to the rhythm of the recently experienced stimulus sequence, the model reliably reproduced MMN-like novelty detection and allowed systematic testing of SCZ-related cellular alterations. Simulations revealed that both reduced pyramidal cell excitability, linked to ion-channel dysfunction, and decreased spine density impaired novelty detection, with the latter producing stronger deficits. Our work provides a flexible spiking network model of auditory novelty detection that can link cellular-level abnormalities to measurable MMN deficits, improving their mechanistic interpretation and helping to explain the heterogeneity of SCZ.

neuroscience↗

Atlas of plasma metabolic markers linked to human brain morphology

The human brain is metabolically demanding, yet the causal interplay between systemic metabolism and brain morphology remains largely unknown. Applying systematic phenome- and genome-wide analyses of 24,940 UK Biobank participants, integrating 249 NMR-derived plasma metabolic markers with MRI-derived brain morphology, we revealed extensive phenotypic associations, with 236 of 249 metabolites linked to at least one global brain measure, including intracranial volume (192 markers), total surface area (183), and mean cortical thickness (139). Distinct regional brain patterns included frontal, temporal, brainstem, and ventricular structures, and the inflammatory marker glycoprotein acetyls showed the strongest individual association, explaining the most variance in global brain measures. We identified extensive genetic overlap, encompassing genes involved in neurodevelopment and stem cell differentiation. Mendelian randomization revealed significant bidirectional causal effects, with metabolic markers predominantly influencing frontal and temporal brain regions. Single cell sequencing data implicated oligodendrocytes and astrocytes mediating the relationships. These findings highlight extensive links between metabolic processes and brain structure, and provide an atlas for understanding the underlying molecular pathways.

neuroscience↗

Genetic mechanisms for impaired synaptic plasticity in schizophrenia revealed by computational modelling

Schizophrenia phenotypes are suggestive of impaired cortical plasticity in the disease, but the mechanisms of these deficits are unknown. Genomic association studies have implicated a large number of genes that regulate neuromodulation and plasticity, indicating that the plasticity deficits have a genetic origin. Here, we used biochemically detailed computational modelling of post-synaptic plasticity to investigate how schizophrenia-associated genes regulate long-term potentiation (LTP) and depression (LTD). We combined our model with data from post-mortem mRNA expression studies (CommonMind gene-expression datasets) to assess the consequences of altered expression of plasticity-regulating genes for the amplitude of LTP and LTD. Our results show that the expression alterations observed post mortem, especially those in anterior cingulate cortex, lead to impaired PKA-pathway-mediated LTP in synapses containing GluR1 receptors. We validated these findings using a genotyped EEG dataset where polygenic risk scores for synaptic and ion channel-encoding genes as well as modulation of visual evoked potentials (VEP) were determined for 286 healthy controls. Our results provide a possible genetic mechanism for plasticity impairments in schizophrenia, which can lead to improved understanding and, ultimately, treatment of the disorder.

neuroscience↗

Abundant pleiotropy across neuroimaging modalities identified through a multivariate genome-wide association study

Genetic pleiotropy is abundant across spatially distributed brain characteristics derived from one neuroimaging modality (e.g. structural, functional or diffusion MRI). A better understanding of pleiotropy across modalities could inform us on the integration of brain function, micro- and macrostructure. Here we show extensive genetic overlap across neuroimaging modalities at a locus and gene level in the UK Biobank (N=34,029) and ABCD Study (N=8,607). When jointly analysing phenotypes derived from structural, functional and diffusion MRI with the Multivariate Omnibus Statistical Test (MOSTest), we boost the discovery of loci and genes beyond previously identified effects for each modality individually. Cross-modality genes are involved in fundamental biological processes and predominantly expressed during prenatal brain development. We additionally boost prediction of psychiatric disorders by conditioning independent GWAS on our multimodal multivariate GWAS. These findings shed light on the shared genetic mechanisms underlying variation in brain morphology, functional connectivity, and tissue composition. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=192 SRC="FIGDIR/small/521181v3_ufig1.gif" ALT="Figure 1"> View larger version (65K): org.highwire.dtl.DTLVardef@1e7eadcorg.highwire.dtl.DTLVardef@ec127eorg.highwire.dtl.DTLVardef@b21f14org.highwire.dtl.DTLVardef@1690c5_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

Multimodal monitoring of human cortical organoids implanted in mice using transparent graphene microelectrodes reveal functional connection between organoid and mouse visual cortex

Human cortical organoids, three-dimensional neuronal cell cultures derived from human induced pluripotent stem cells, have recently emerged as promising models of human brain development and dysfunction. Transplantation of human brain organoids into the mouse brain has been shown to be a successful in vivo model providing vascularization for long term chronic experiments. However, chronic functional connectivity and responses evoked by external sensory stimuli has yet to be demonstrated, due to limitations of chronic recording technologies. Here, we develop an experimental paradigm based on transparent graphene microelectrode arrays and two-photon imaging for longitudinal, multimodal monitoring of human organoids transplanted in the mouse cortex. The transparency of graphene microelectrodes permits visual and optical inspection of the transplanted organoid and the surrounding cortex throughout the chronic experiments where local field potentials and multi-unit activity (MUA) are recorded during spontaneous activity and visual stimuli. These experiments reveal that visual stimuli evoke electrophysiological responses in the organoid, matching the responses from the surrounding cortex. Increases in the power of the gamma and MUA bands as well as phase locking of MUA events to slow oscillations evoked by visual stimuli suggest functional connectivity established between the human and mouse tissue. Optical imaging through the transparent microelectrodes shows vascularization of the organoids. Postmortem histological analysis exhibits morphological integration and synaptic connectivity with surrounding mouse cortex as well as migration of organoid cells into the surrounding cortex. This novel combination of stem cell and neural recording technologies could serve as a unique platform for comprehensive evaluation of organoids as models of brain development and dysfunction and as personalized neural prosthetics to restore lost, degenerated, or damaged brain regions.

neuroscience↗

Multivariate genetic analysis of personality and cognitive traits reveals abundant pleiotropy and improves prediction

Personality and cognition are heritable mental traits, and their genetic determinants may be distributed across interconnected brain functions. However, previous studies have employed univariate approaches which reduce complex traits to summary measures. We applied the "pleiotropy-informed" multivariate omnibus statistical test (MOSTest) to genome-wide association studies (GWAS) of 35 item and task-level measures of neuroticism and cognition from the UK Biobank (n=336,993). We identified 431 significant genetic loci and found evidence of abundant pleiotropy across personality and cognitive domains. Functional characterisation implicated genes with significant tissue-specific expression in all tested brain tissues and enriched in brain-specific gene-sets. We conditioned independent GWAS of the Big 5 personality traits and cognition on our multivariate findings, which boosted genetic discovery in other personality traits and improved polygenic prediction. These findings advance our understanding of the polygenic architecture of complex mental traits, indicating a prominence of pleiotropic genetic effects across higher-order domains of mental function. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/481967v2_ufig1.gif" ALT="Figure 1"> View larger version (89K): org.highwire.dtl.DTLVardef@1641108org.highwire.dtl.DTLVardef@9a24eeorg.highwire.dtl.DTLVardef@1eeae99org.highwire.dtl.DTLVardef@108db7f_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

Loss-of-function variants in the schizophrenia risk gene SETD1A alter neuronal network activity in human neurons through cAMP/PKA pathway

Heterozygous loss-of-function (LoF) mutations in SETD1A, which encodes a subunit of histone H3 lysine 4 methyltransferase, were shown to cause a novel neurodevelopmental syndrome and increase the risk for schizophrenia. We generated excitatory/inhibitory neuronal networks from human induced pluripotent stem cells with a SETD1A heterozygous LoF mutation (SETD1A+/-) using CRISPR/Cas9. Our data show that SETD1A haploinsufficiency resulted in morphologically increased dendritic complexity and functionally increased bursting activity. This network phenotype was primarily driven by SETD1A haploinsufficiency in glutamatergic neurons. In accordance with the functional changes, transcriptomic profiling revealed perturbations in gene sets associated with glutamatergic synaptic function. At the molecular level, we identified specific changes in the cAMP/PKA pathway pointing toward a hyperactive cAMP pathway in SETD1A+/- neurons. Finally, by pharmacologically targeting the cAMP pathway we were able to rescue the network deficits in SETD1A+/- cultures. Our results demonstrate a link between SETD1A and the cAMP-dependent pathway in human neurons.

neuroscience↗

All-optical electrophysiology in hiPSC-derived neurons with synthetic voltage sensors

Voltage imaging and "all-optical electrophysiology" in human induced pluripotent stem cell (hiPSC)-derived neurons have opened unprecedented opportunities for high-throughput phenotyping of activity in neurons possessing unique genetic backgrounds of individual patients. While prior all-optical electrophysiology studies relied on genetically encoded voltage indicators, viral transduction of human neurons with large or multiple expression vectors can impact cell function and often lead to massive cell death. Here, we demonstrate an alternative protocol using a synthetic voltage sensor and genetically encoded optogenetic actuator that generate robust and reproducible results. We demonstrate the functionality of this method by measuring spontaneous and evoked activity in three independent hiPSC-derived neuronal cell lines with distinct genetic backgrounds.

neuroscience↗

A human iPSC-astroglia neurodevelopmental model reveals divergent transcriptomic patterns in schizophrenia

While neurodevelopmental abnormalities have been associated with schizophrenia (SCZ), the role of astroglia in disease pathophysiology remains poorly understood. In this study we used a human induced pluripotent stem cell (iPSC)-derived astrocyte model to investigate the temporal patterns of astroglia differentiation during developmental stages critical for SCZ using RNA-sequencing. The model generated astrocyte-specific patterns of gene expression during differentiation, and demonstrated that these patterns correspond well to astroglia-specific expression signatures of in vivo cortical fetal development. Applying this model, we were able to identify SCZ-specific expression dynamics in human astrocytes, and found that SCZ-associated differentially expressed genes were significantly enriched in the medial prefrontal cortex, striatum, and temporal lobe, targeting VWA5A and ADAMTS19. In addition, SCZ astrocytes displayed alterations in calcium signaling, and significantly decreased glutamate uptake and metalloproteinase activity relative to controls. These results provide strong support for the validity of our astrocyte model, and implicate novel transcriptional dynamics in astrocyte differentiation in SCZ together with functional changes that are potentially important biological components of SCZ pathology.

neuroscience↗

Identifying Nootropic Drug Targets via Large-Scale Cognitive GWAS and Transcriptomics

BackgroundCognitive traits demonstrate significant genetic correlations with many psychiatric disorders and other health-related traits. Many neuropsychiatric and neurodegenerative disorders are marked by cognitive deficits. Therefore, genome-wide association studies (GWAS) of general cognitive ability might suggest potential targets for nootropic drug repurposing. Our previous effort to identify "druggable genes" (i.e., GWAS-identified genes that produce proteins targeted by known small molecules) was modestly powered due to the small cognitive GWAS sample available at the time. Since then, two large cognitive GWAS meta-analyses have reported 148 and 205 genome-wide significant loci, respectively. Additionally, large-scale gene expression databases, derived from post-mortem human brain, have recently been made available for GWAS annotation. Here, we 1) reconcile results from these two cognitive GWAS meta-analyses to further enhance power for locus discovery; 2) employ several complementary transcriptomic methods to identify genes in these loci with variants that are credibly associated with cognition; and 3) further annotate the resulting genes to identify "druggable" targets. MethodsGWAS summary statistics were harmonized and jointly analysed using Multi-Trait Analysis of GWAS [MTAG], which is optimized for handling sample overlaps. Downstream gene identification was carried out using MAGMA, S-PrediXcan/S-TissueXcan Transcriptomic Wide Analysis, and eQTL mapping, as well as more recently developed methods that integrate GWAS and eQTL data via Summary-statistics Mendelian Randomization [SMR] and linkage methods [HEIDI], Available brain-specific eQTL databases included GTEXv7, BrainEAC, CommonMind, ROSMAP, and PsychENCODE. Intersecting credible genes were then annotated against multiple chemoinformatic databases [DGIdb, KI, and a published review on "druggability"]. ResultsUsing our meta-analytic data set (N = 373,617) we identified 241 independent cognition-associated loci (29 novel), and 76 genes were identified by 2 or more methods of gene identification. 26 genes were associated with general cognitive ability via SMR, 16 genes via STissueXcan/S-PrediXcan, 47 genes via eQTL mapping, and 68 genes via MAGMA pathway analysis. The use of the HEIDI test permitted the exclusion of candidate genes that may have been artifactually associated to cognition due to linkage, rather than direct causal or indirect pleiotropic effects. Actin and chromatin binding gene sets were identified as novel pathways that could be targeted via drug repurposing. Leveraging on our various transcriptome and pathway analyses, as well as available chemoinformatic databases, we identified 16 putative genes that may suggest drug targets with nootropic properties. DiscussionResults converged on several categories of significant drug targets, including serotonergic and glutamatergic genes, voltage-gated ion channel genes, carbonic anhydrase genes, and phosphodiesterase genes. The current results represent the first efforts to apply a multi-method approach to integrate gene expression and SNP level data to identify credible actionable genes for general cognitive ability.

genomics↗

The genetic architecture of human brainstem structures and their involvement in common brain disorders

Brainstem regions support critical bodily functions, yet their genetic architectures and involvement in brain disorders remain understudied. Here, we examined volumes of brainstem structures using magnetic resonance imaging in 43,353 individuals. In 27,034 genotyped healthy participants, we identified 16 genetic loci associated with whole brainstem volume and 10, 23, 3, and 9 loci associated with volumes of the midbrain, pons, superior cerebellar peduncle, and medulla oblongata, respectively. These loci were mapped to 305 genes, including genes linked to brainstem development and common brain disorders. We detected genetic overlap between the brainstem volumes and eight psychiatric and neurological disorders. Using imaging data from 16,319 additional individuals, we observed differential volume alterations in schizophrenia, bipolar disorder, multiple sclerosis, mild cognitive impairment, dementia, and Parkinsons disease. Together, our results provide new insights into the genetic underpinnings of brainstem structures and support their involvement in common brain disorders.

neuroscience↗

Cannabis use is associated with increased levels of soluble gp130 in schizophrenia but not in bipolar disorder

The complex effects of plant cannabinoids on human physiology is not yet fully understood, but include a wide spectrum of effects on immune modulation. The immune system and its inflammatory effector pathways are recently emerging as possible causative factors in psychotic disorders. The present study aimed to investigate whether self-administered cannabis use was associated with changes in circulating immune and neuroendocrine markers in schizophrenia (SCZ, n=401) and bipolar disorder patients (BD, n=242). A screening of 13 plasma markers reflecting different inflammatory pathways was performed in SCZ and BD patients after subdividing each group into cannabis user and non-user subgroups. We found that i) soluble gp130 (sgp130) concentrations were significantly elevated among cannabis users in the SCZ group (p=0.002) after multiple testing correction, but not in BD. ii) Nominally significant differences were observed in the levels of IL-1RA (p=0.0059), YKL40 (p=0.0069), CatS (p=0.013), sTNFR1 (p=0.031), and BDNF (p=0.020), where these factors exhibited higher plasma levels in cannabis user SCZ patients than in non-users. iii) These differences in systemic levels were not reflected by altered mRNA expression of genes encoding sgp130, IL-1RA, YKL40, CatS, sTNFR1, and BDNF in whole blood. In sum, our results show that cannabis self-administration is associated with markedly higher sgp130 levels in SCZ, but not in BD, and that this phenomenon is independent of the modulation of peripheral immune cells. These findings warrant further investigation into the potential neuroimmune, anti-inflammatory, and biobehavioral-cognitive effects of cannabis use in SCZ.

pharmacology and toxicology↗

Annotation-Informed Causal Mixture Modeling (AI-MiXeR) reveals phenotype-specific differences in polygenicity and effect size distribution across functional annotation categories

Determining the contribution of functional genetic categories is fundamental to understanding the genetic etiology of complex human traits and diseases. Here we present Annotation Informed MiXeR: a likelihood-based method to estimate the number of variants influencing a phenotype and their effect sizes across different functional annotation categories of the genome using summary statistics from genome-wide association studies. Applying the model to 11 complex phenotypes suggests diverse patterns of functional category-specific genetic architectures across human diseases and traits.

genetics↗

Association between schizophrenia polygenic score and psychotic symptoms in Alzheimer disease: meta-analysis of 10 cohort studies

BackgroundPsychosis (delusions and hallucinations) is common in Alzheimers disease (AD) and associated with worse clinical outcomes including accelerated cognitive decline and shorter time to nursing home admission. Atypical antipsychotics have limited efficacy which, along with emerging genomic research, suggests some overlapping mechanisms with other disorders characterized by psychosis, like schizophrenia. In this study, we tested whether polygenic risk score (PRS) for schizophrenia was associated with psychotic symptoms in AD. MethodsSchizophrenia PRS was calculated using Psychiatric Genomics Consortium data at 10 GWAS p-value thresholds (PT) in 3,173 AD cases from 11 cohort studies. Association between PRS and AD psychosis status was tested by logistic regression in each cohort individually and the results meta-analyzed. ResultsThe schizophrenia PRS was associated with psychosis in AD at an optimum PT of The strongest association was for delusions where a one standard deviation increase in PRS was associated with a 1.17-fold increased risk (95% CI: 1.07-1.3; p=0.001). ConclusionThese new findings point towards psychosis in AD - and particularly delusions - sharing some genetic liability with schizophrenia, and support a transdiagnostic view of psychotic symptoms across the lifespan.

genomics↗

Pleiotropic Meta-Analysis of Cognition, Education, and Schizophrenia Differentiates Roles of Early Neurodevelopmental and Adult Synaptic Pathways

Liability to schizophrenia is inversely correlated with general cognitive ability at both the phenotypic and genetic level. Paradoxically, a modest but consistent positive genetic correlation has been reported between schizophrenia and educational attainment, despite the strong positive genetic correlation between cognitive ability and educational attainment. Here we leverage published GWAS in cognitive ability, education, and schizophrenia to parse biological mechanisms underlying these results. Association analysis based on subsets (ASSET), a pleiotropic meta-analytic technique, allowed jointly associated loci to be identified and characterized. Specifically, we identified subsets of variants associated in the expected (\"Concordant\") direction across all three phenotypes (i.e., greater risk for schizophrenia, lower cognitive ability, and lower educational attainment); these were contrasted with variants demonstrating the counterintuitive (\"Discordant\") relationship between education and schizophrenia (i.e., greater risk for schizophrenia and higher educational attainment). ASSET analysis revealed 235 independent loci associated with cognitive ability, education and/or schizophrenia at p<5x10-8. Pleiotropic analysis successfully identified more than 100 loci that were not significant in the input GWASs, and many of these have been validated by larger, more recent single-phenotype GWAS. Leveraging the joint genetic correlations of cognitive ability, education, and schizophrenia, we were able to dissociate two distinct biological mechanisms: early neurodevelopmental pathways that characterize concordant allelic variation, and adulthood synaptic pruning pathways that were linked to the paradoxical positive genetic association between education and schizophrenia. Further, genetic correlation analyses revealed that these mechanisms contribute not only to the etiopathogenesis of schizophrenia, but also to the broader biological dimensions that are implicated in both general health outcomes and psychiatric illness.

genetics↗