Gene Expression In Brain Tissue Research Articles

Genome-Wide Epistatic Network Analyses of Semantic Fluency in Older Adults.

Semantic fluency impairment has been attributed to a wide range of neurocognitive and psychiatric conditions, especially in the older population. Moderate heritability estimates on semantic fluency were obtained from both twin and family-based studies suggesting genetic contributions to the observed variation across individuals. Currently, effort in identifying the genetic variants underlying the heritability estimates for this complex trait remains scarce. Using the semantic fluency scale and genome-wide SNP genotype data from the Long Life Family Study (LLFS), we performed a genome-wide association study (GWAS) and epistasis network analysis on semantic fluency in 2289 individuals aged over 60 years from the American LLFS cohorts and replicated the findings in 1129 individuals aged over 50 years from the Danish LLFS cohort. In the GWAS, two SNPs with genome-wide significance (rs3749683, p = 2.52 × 10-8; rs880179, p = 4.83 × 10-8) mapped to the CMYAS gene on chromosome 5 were detected. The epistasis network analysis identified five modules as significant (4.16 × 10-5 < p < 7.35 × 10-3), of which two were replicated (p < 3.10 × 10-3). These two modules revealed significant enrichment of tissue-specific gene expression in brain tissues and high enrichment of GWAS catalog traits, e.g., obesity-related traits, blood pressure, chronotype, sleep duration, and brain structure, that have been reported to associate with verbal performance in epidemiological studies. Our results suggest high tissue specificity of genetic regulation of gene expression in brain tissues with epistatic SNP networks functioning jointly in modifying individual verbal ability and cognitive performance.

Mendelian Randomization Applied to Neurology: Promises and Challenges

The Mendelian randomization (MR) paradigm allows for causal inferences to be drawn using genetic data. In recent years, the expansion of well-powered publicly available genetic association data related to phenotypes such as brain tissue gene expression, brain imaging, and neurologic diseases offers exciting opportunities for the application of MR in the field of neurology. In this review, we discuss the basic principles of MR, its myriad applications to research in neurology, and potential pitfalls of injudicious applications. Throughout, we provide examples where MR-informed findings have shed light on long-standing epidemiologic controversies, provided insights into the pathophysiology of neurologic conditions, prioritized drug targets, and informed drug repurposing opportunities. With the ever-expanding availability of genome-wide association data, we project MR to become a key driver of progress in the field of neurology. It is therefore paramount that academics and clinicians within the field are familiar with the approach.

Exploring JC polyomavirus sequences and human gene expression in brain tissue of patients with progressive multifocal leukoencephalopathy.

Progressive multifocal leukoencephalopathy (PML) is a rare neurological condition associated with reactivation of dormant JC polyomavirus (JCPyV). In this study, we characterized gene expression and JCPyV rearrangements in PML brain tissue. Infection of white matter astrocytes and oligodendrocytes as well as occasional brain cortex neurons was shown. PML brain harbored exclusively rearranged JCPyV variants. Viral transcripts covered the whole genome on both strands. Strong differential expression of human genes associated with neuroinflammation, blood-brain-barrier permeability and neurodegenerative diseases was shown. Pathway analysis revealed wide immune activation in PML brain. The study provides novel insights into the pathogenesis of PML.

Circulatory proteins relate cardiovascular disease to cognitive performance: a Mendelian randomisation study

AbstractBackgroundMechanistic research suggests synergistic effects of cardiovascular disease (CVD) and dementia pathologies on cognitive decline. The objective of this study was to investigate the causal relationship between cardiovascular disease (CVD) related proteins and cognitive decline.MethodWe applied Mendelian randomisation (MR) and colocalization analysis to investigate the causal relationships of 90 CVD‐related proteins measured by the Olink CVD I panel with cognitive traits. Genetic instruments for circulatory protein concentrations were obtained from a genome‐wide association study (GWAS) meta‐analysis from the SCALLOP consortium (N = 17,747) based on three sets of criteria: 1) protein quantitative trait loci (pQTL); 2) cis‐pQTL (pQTL within ±500kb from the coding gene); and 3) brain‐specific cis‐expression QTL (cis‐eQTL) which accounts for coding gene expression based on GTEx8. Genetic associations of cognitive performance were obtained from GWAS for either: 1) general cognitive function constructed using Principal Component Analysis (N = 300,486); or, 2) g‐Factor constructed using genomic structural equation modelling (N = 11,263‐331,679). Findings for candidate causal proteins were replicated using a separate protein GWAS in Icelanders (N = 35,559).ResultA higher concentration of genetically predicted circulatory myeloperoxidase (MPO) was nominally associated with better cognitive performance (P&lt;0.05) using different selection criteria for genetic instruments. Particularly, brain‐specific cis‐eQTL predicted MPO, which accounts for protein coding gene expression in brain tissues, was associated with general cognitive function (βWald = 0.22, PWald = 2.4×10−4). The posterior probability for colocalization (PP.H4) of MPO pQTL with the g Factor was 0.58. Findings for MPO were replicated using a GWAS on cognitive score in an Icelandic population. Although we did not find evidence for colocalization, we found that higher genetically predicted concentrations of cathepsin D and CD40 were associated with better cognitive performance and higher genetically predicted concentration of CSF‐1 were associated with poorer cognitive performance.ConclusionThe study suggests that proteins primarily identified for their role in cardiovascular diseases may be involved in shared pathways with cognitive reserve or cognitive decline, and may confer therapeutic targets for neurodegenerative diseases such as Alzheimer’s disease.

Protective effect of exogenous peroxiredoxin 6 and thymic peptide thymulin on BBB conditions in an experimental model of multiple sclerosis

This study aimed to assess the effects of the immunomodulator thymulin, a thymic peptide with anti-inflammatory effects, and peroxiredoxin 6 (Prdx6), an antioxidant enzyme with dual peroxidase and phospholipase A2 activities, on the blood‒brain barrier (BBB) condition and general health status of animals with relapsing-remitting experimental autoimmune encephalomyelitis (EAE), which is a model of multiple sclerosis in humans. Both thymulin and Prdx6 significantly improved the condition of the BBB, which was impaired by EAE induction, as measured by Evans blue dye accumulation, tight-junction protein loss in brain tissue, and lymphocyte infiltration through the BBB. The effect was associated with significant amelioration of EAE symptoms. Thymulin treatment was accompanied by a decrease in immune cell activation as judged by interleukin-6, -17, and interferon-gamma cytokine levels in serum and NF-kappaB cascade activation in splenocytes of mice with EAE. Prdx6 did not induce significant immunomodulatory effects but abruptly decreased EAE-induced NOX1 and NOX4 gene expression in brain tissue, which may be one of the possible mechanisms of its beneficial effects on BBB conditions and health status. The simultaneous administration of thymulin and Prdx6 resulted in complete symptomatic restoration of mice with EAE. The results demonstrate prospective strategies for multiple sclerosis treatment.

Circulatory proteins relate cardiovascular disease to cognitive performance: A mendelian randomisation study.

Background and objectives: Mechanistic research suggests synergistic effects of cardiovascular disease (CVD) and dementia pathologies on cognitive decline. Interventions targeting proteins relevant to shared mechanisms underlying CVD and dementia could also be used for the prevention of cognitive impairment. Methods: We applied Mendelian randomisation (MR) and colocalization analysis to investigate the causal relationships of 90 CVD-related proteins measured by the Olink CVD I panel with cognitive traits. Genetic instruments for circulatory protein concentrations were obtained using a meta-analysis of genome-wide association studies (GWAS) from the SCALLOP consortium (N = 17,747) based on three sets of criteria: 1) protein quantitative trait loci (pQTL); 2) cis-pQTL (pQTL within ±500kb from the coding gene); and 3) brain-specific cis-expression QTL (cis-eQTL) which accounts for coding gene expression based on GTEx8. Genetic associations of cognitive performance were obtained from GWAS for either: 1) general cognitive function constructed using Principal Component Analysis (N = 300,486); or, 2) g Factor constructed using genomic structural equation modelling (N = 11,263-331,679). Findings for candidate causal proteins were replicated using a separate protein GWAS in Icelanders (N = 35,559). Results: A higher concentration of genetically predicted circulatory myeloperoxidase (MPO) was nominally associated with better cognitive performance (p < 0.05) using different selection criteria for genetic instruments. Particularly, brain-specific cis-eQTL predicted MPO, which accounts for protein-coding gene expression in brain tissues, was associated with general cognitive function (βWald = 0.22, PWald = 2.4 × 10-4). The posterior probability for colocalization (PP.H4) of MPO pQTL with the g Factor was 0.577. Findings for MPO were replicated using the Icelandic GWAS. Although we did not find evidence for colocalization, we found that higher genetically predicted concentrations of cathepsin D and CD40 were associated with better cognitive performance and a higher genetically predicted concentration of CSF-1 was associated with poorer cognitive performance. Conclusion: We conclude that these proteins are involved in shared pathways between CVD and those for cognitive reserve or affecting cognitive decline, suggesting therapeutic targets able to reduce genetic risks conferred by cardiovascular disease.

Retrotransposon insertions associated with risk of neurologic and psychiatric diseases.

Transposable elements (TEs) are active in neuronal cells raising the question whether TE insertions contribute to risk of neuropsychiatric disease. While genome-wide association studies (GWAS) serve as a tool to discover genetic loci associated with neuropsychiatric diseases, unfortunately GWAS do not directly detect structural variants such as TEs. To examine the role of TEs in psychiatric and neurologic disease, we evaluated 17,000 polymorphic TEs and find 76 are in linkage disequilibrium with disease haplotypes (P < 10-6 ) defined by GWAS. From these 76 polymorphic TEs, we identify potentially causal candidates based on having insertions in genomic regions of regulatory chromatin and on having associations with altered gene expression in brain tissues. We show that lead candidate insertions have regulatory effects on gene expression in human neural stem cells altering the activity of a minimal promoter. Taken together, we identify 10 polymorphic TE insertions that are potential candidates on par with other variants for having a causal role in neurologic and psychiatric disorders.

Abstract WMP80: Pleiotropy Analyses Of Between Intracerebral Hemorrhage And β-amyloid Related Phenotypes

Introduction: Combining biologically related traits in genome-wide association studies has been demonstrated to increase the power for genetic discovery and to identify new genes associated with intracerebral hemorrhage (ICH). Given the pathological relationship between lobar ICH and cerebral amyloid angiopathy (CAA), and between the latter and levels of CSF amyloid-β 42 (CSF-Aβ 42 ), we leveraged genetic predisposition for lower CSF Aβ 42 levels, as a proxy phenotype for CAA, in pleiotropy analysis for lobar ICH. Methods: We used publicly available GWAS data for Aβ 42 levels (n=3,146) and for lobar ICH (n=1,813) from the International Stroke Genetics Consortium. To evaluate the association between lobar ICH risk and CSF-Aβ 42 , we computed a polygenic risk score (PRS) for CSF-Aβ 42 in lobar ICH patients. We then applied multi-trait analysis of GWAS (MTAG) for pleiotropy analysis of lobar ICH and CSF-Aβ 42 . Gene-level associations based on the MTAG result were further tested using S-Predixcan. Results: We found a significant association between CSF-Aβ 42 PRS and ICH risk (β = -0.35; P = 0.04). MTAG analyses identified one novel near-genome-wide significant association within CDH9 (rs1007589; minor allele frequency=0.09; MTAG β = -0.12 and P = 5.4x10 -8 ; lobar ICH β = 0.34 and P = 2.4x10 -3 ; CSF-Aβ 42 β = -0.03 and P = 4.5x10 -6 ). According to the BRAINEAC brain tissue gene expression database, rs1007589 is significantly associated with increased expression of CDH9 in both temporal and occipital cortices. Discussion: This pleiotropy analysis was designed to identify genetic determinants of lobar ICH driven by amyloid-related mechanisms. We identified a variant in one novel gene associated with both traits, CDH9 , which causes differential expression in two brain regions characteristically affected by vascular amyloid pathology. CDH9 encodes for one subtype of the cadherin superfamily, which regulates intercellular adhesion. Cadherins have been involved in blood-brain barrier integrity and are elevated in AD patients. Further analyses are warranted to understand the effects of the variant on the pathogenesis of ICH and its clinical significance.

Harnessing tissue-specific genetic variation to dissect putative causal pathways between body mass index and cardiometabolic phenotypes

Body mass index (BMI) is a complex disease risk factor known to be influenced by genes acting via both metabolic pathways and appetite regulation. In this study, we aimed to gain insight into the phenotypic consequences of BMI-associated genetic variants, which may be mediated by their expression in different tissues. First, we harnessed meta-analyzed gene expression datasets derived from subcutaneous adipose (n = 1257) and brain (n = 1194) tissue to identify 86 and 140 loci, respectively, which provided evidence of genetic colocalization with BMI. These two sets of tissue-partitioned loci had differential effects with respect to waist-to-hip ratio, suggesting that the way they influence fat distribution might vary despite their having very similar average magnitudes of effect on BMI itself (adipose = 0.0148 and brain = 0.0149 standard deviation change in BMI per effect allele). For instance, BMI-associated variants colocalized with TBX15 expression in adipose tissue (posterior probability [PPA] = 0.97), but not when we used TBX15 expression data derived from brain tissue (PPA = 0.04) This gene putatively influences BMI via its role in skeletal development. Conversely, there were loci where BMI-associated variants provided evidence of colocalization with gene expression in brain tissue (e.g., NEGR1, PPA = 0.93), but not when we used data derived from adipose tissue, suggesting that these genes might be more likely to influence BMI via energy balance. Leveraging these tissue-partitioned variant sets through a multivariable Mendelian randomization framework provided strong evidence that the brain-tissue-derived variants are predominantly responsible for driving the genetically predicted effects of BMI on cardiovascular-disease endpoints (e.g., coronary artery disease: odds ratio = 1.05, 95% confidence interval = 1.04-1.07, p= 4.67× 10-14). In contrast, our analyses suggested that the adipose tissue variants might predominantly be responsible for the underlying relationship between BMI and measures of cardiac function, such as left ventricular stroke volume (beta = 0.21, 95% confidence interval = 0.09-0.32, p = 6.43× 10-4).

Deep learning-based brain transcriptomic signatures associated with the neuropathological and clinical severity of Alzheimer's disease.

Brain tissue gene expression from donors with and without Alzheimer’s disease has been used to help inform the molecular changes associated with the development and potential treatment of this disorder. Here, we use a deep learning method to analyse RNA-seq data from 1114 brain donors from the Accelerating Medicines Project for Alzheimer’s Disease consortium to characterize post-mortem brain transcriptome signatures associated with amyloid-β plaque, tau neurofibrillary tangles and clinical severity in multiple Alzheimer’s disease dementia populations. Starting from the cross-sectional data in the Religious Orders Study and Memory and Aging Project cohort (n = 634), a deep learning framework was built to obtain a trajectory that mirrors Alzheimer’s disease progression. A severity index was defined to quantitatively measure the progression based on the trajectory. Network analysis was then carried out to identify key gene (index gene) modules present in the model underlying the progression. Within this data set, severity indexes were found to be very closely correlated with all Alzheimer’s disease neuropathology biomarkers (R ∼ 0.5, P < 1e−11) and global cognitive function (R = −0.68, P < 2.2e−16). We then applied the model to additional transcriptomic data sets from different brain regions (MAYO, n = 266; Mount Sinai Brain Bank, n = 214), and observed that the model remained significantly predictive (P < 1e−3) of neuropathology and clinical severity. The index genes that significantly contributed to the model were integrated with Alzheimer’s disease co-expression regulatory networks, resolving four discrete gene modules that are implicated in vascular and metabolic dysfunction in different cell types, respectively. Our work demonstrates the generalizability of this signature to frontal and temporal cortex measurements and additional brain donors with Alzheimer’s disease, other age-related neurological disorders and controls, and revealed that the transcriptomic network modules contribute to neuropathological and clinical disease severity. This study illustrates the promise of using deep learning methods to analyse heterogeneous omics data and discover potentially targetable molecular networks that can inform the development, treatment and prevention of neurodegenerative diseases like Alzheimer’s disease.

EASI-FISH for thick tissue defines lateral hypothalamus spatio-molecular organization

Determining the spatial organization and morphological characteristics of molecularly defined cell types is a major bottleneck for characterizing the architecture underpinning brain function. We developed Expansion-Assisted Iterative Fluorescence In Situ Hybridization (EASI-FISH) to survey gene expression in brain tissue, as well as a turnkey computational pipeline to rapidly process large EASI-FISH image datasets. EASI-FISH was optimized for thick brain sections (300μm) to facilitate reconstruction of spatio-molecular domains that generalize across brains. Using the EASI-FISH pipeline, we investigated the spatial distribution of dozens of molecularly defined cell types in the lateral hypothalamic area (LHA), a brain region with poorly defined anatomical organization. Mapping cell types in the LHA revealed nine spatially and molecularly defined subregions. EASI-FISH also facilitates iterative reanalysis of scRNA-seq datasets to determine marker-genes that further dissociated spatial and morphological heterogeneity. The EASI-FISH pipeline democratizes mapping molecularly defined cell types, enabling discoveries about brain organization.

Interdependence of neural network dysfunction and microglial alterations in Alzheimer’s disease-related models

SummaryNonconvulsive epileptiform activity and microglial alterations have been detected in people with Alzheimer’s disease (AD) and related mouse models. However, the relationship between these abnormalities remains to be elucidated. We suppressed epileptiform activity by treatment with the antiepileptic drug levetiracetam or by genetic ablation of tau and found that these interventions reversed or prevented aberrant microglial gene expression in brain tissues of aged human amyloid precursor protein transgenic mice, which simulate several key aspects of AD. The most robustly modulated genes included multiple factors previously implicated in AD pathogenesis, including TREM2, the hypofunction of which increases disease risk. Genetic reduction of TREM2 exacerbated epileptiform activity after mice were injected with kainate. We conclude that AD-related epileptiform activity markedly changes the molecular profile of microglia, inducing both maladaptive and adaptive alterations in their activities. Increased expression of TREM2 seems to support microglial activities that counteract this type of network dysfunction.

Effect of Xenon Treatment on Gene Expression in Brain Tissue after Traumatic Brain Injury in Rats.

The overactivation of inflammatory pathways and/or a deficiency of neuroplasticity may result in the delayed recovery of neural function in traumatic brain injury (TBI). A promising approach to protecting the brain tissue in TBI is xenon (Xe) treatment. However, xenon’s mechanisms of action remain poorly clarified. In this study, the early-onset expression of 91 target genes was investigated in the damaged and in the contralateral brain areas (sensorimotor cortex region) 6 and 24 h after injury in a TBI rat model. The expression of genes involved in inflammation, oxidation, antioxidation, neurogenesis and neuroplasticity, apoptosis, DNA repair, autophagy, and mitophagy was assessed. The animals inhaled a gas mixture containing xenon and oxygen (ϕXe = 70%; ϕO2 25–30% 60 min) 15–30 min after TBI. The data showed that, in the contralateral area, xenon treatment induced the expression of stress genes (Irf1, Hmox1, S100A8, and S100A9). In the damaged area, a trend towards lower expression of the inflammatory gene Irf1 was observed. Thus, our results suggest that xenon exerts a mild stressor effect in healthy brain tissue and has a tendency to decrease the inflammation following damage, which might contribute to reducing the damage and activating the early compensatory processes in the brain post-TBI.

Chronic Exposure to Two Gestagens Differentially Alters Morphology and Gene Expression in Silurana tropicalis.

Gestagens are active ingredients in human and veterinary drugs with progestogenic activity. Two gestagens-progesterone (P4), and the synthetic P4 analogue, melengestrol acetate (MGA)-are approved for use in beef cattle agriculture in North America. Both P4 and MGA have been measured in surface water receiving runoff from animal agricultural operations. This project aimed to assess the morphometric and molecular consequences of chronic exposures to P4, MGA, and their mixture during Western clawed frog metamorphosis. Chronic exposure (from embryo to metamorphosis) to MGA (1.7µg/L) or P4 + MGA (0.22µg/L P4 + 1.5µg/L MGA) caused a considerable dysregulation of metamorphic timing, as evidenced by an inhibition of growth, narrower head, and lack of forelimb emergence in all animals. Molecular analysis revealed that chronic exposure to the mixture induced an additive upregulation of neurosteroid-related (GABAA receptor subunit α6 (gabra6) and steroid 5-alpha reductase 1 (srd5α1) gene expression in brain tissue. Chronic P4 exposure (0.26µg/L P4) induced a significant upregulation of the expression hypothalamic-pituitary-gonadal (HPG)-related genes (ipgr, erα) in the gonadal mesonephros complex (GMC). Our data suggest that exposure to P4, MGA, and their mixture induces multiple endocrine responses and adverse effects in larval Western clawed frogs. This study helps to better our understanding of the consequences of chronic gestagen exposure and suggests that the implications and risk of high gestagen use in beef cattle feeding operations may extend to the aquatic environment.

Potential Genes and Mechanisms Linking Intracerebral Hemorrhage and Depression: A Bioinformatics-Based Study.

PurposeThe purpose of this study was to investigate the potential pathogenic mechanisms of post-intracerebral hemorrhage depression.MethodsProfiles of gene expression in brain tissue of patients with intracerebral hemorrhage (ICH) or depression were downloaded from the Gene Expression Omnibus (GEO) database. We analyzed differentially expressed genes (DEGs) for the two diseases separately. With these DEGs, we conducted an enrichment analysis based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) as well as cross-talk analysis, then we identified hub bridge genes using integrated bridge landscape analysis.ResultsWe found 131 DEGs for interaction between ICH and depression. In the enrichment analysis, we found 55 GO terms and KEGG pathways involving interacting genes of ICH and depression, and 10 GO terms and 10 KEGG pathways most significantly related to cross-talk between ICH and depression. In the integrated bridge landscape analysis, we identified 20 hub bridge genes. In further analysis, we found that hub bridge genes HLA-A, HMOX1, and JUN related to endocytosis, cell adhesion, and phagosomes may exert their effects through the dopamine (DA) system and the serotonergic pathway post-ICH depression. HLA-A may play a role in the occurrence and development of ICH and depression through immune mediation and cell adhesion. HMOX1 and JUN may participate in the mechanism by interacting with HLA-A.ConclusionThrough bioinformatics analysis, we identified potential hub bridge genes and pathways related to post-ICH depression. Our study provides references for further research on mechanisms on the pathogenesis of post-ICH depression.

Brain activity and transcriptional profiling in mice under chronic jet lag

Shift work is known to be associated with an increased risk of neurological and psychiatric diseases, but how it contributes to the development of these diseases remains unclear. Chronic jet lag (CJL) induced by shifting light-dark cycles repeatedly is a commonly used protocol to mimic the environmental light/dark changes encountered by shift workers. Here we subjected wildtype mice to CJL and performed positron emission tomography imaging of glucose metabolism to monitor brain activities. We also conducted RNA sequencing using prefrontal cortex and nucleus accumbens tissues from these animals, which are brain regions strongly implicated in the pathology of various neurological and psychiatric conditions. Our results reveal the alterations of brain activities and systematic reprogramming of gene expression in brain tissues under CJL, building hypothesis for how CJL increases the susceptibility to neurological and psychiatric diseases.

Identifying and validating subtypes within major psychiatric disorders based on frontal–posterior functional imbalance via deep learning

Converging evidence increasingly implicates shared etiologic and pathophysiological characteristics among major psychiatric disorders (MPDs), such as schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD). Examining the neurobiology of the psychotic-affective spectrum may greatly advance biological determination of psychiatric diagnosis, which is critical for the development of more effective treatments. In this study, ensemble clustering was developed to identify subtypes within a trans-diagnostic sample of MPDs. Whole brain amplitude of low-frequency fluctuations (ALFF) was used to extract the low-dimensional features for clustering in a total of 944 participants: 581 psychiatric patients (193 with SZ, 171 with BD, and 217 with MDD) and 363 healthy controls (HC). We identified two subtypes with differentiating patterns of functional imbalance between frontal and posterior brain regions, as compared to HC: (1) Archetypal MPDs (60% of MPDs) had increased frontal and decreased posterior ALFF, and decreased cortical thickness and white matter integrity in multiple brain regions that were associated with increased polygenic risk scores and enriched risk gene expression in brain tissues; (2) Atypical MPDs (40% of MPDs) had decreased frontal and increased posterior ALFF with no associated alterations in validity measures. Medicated Archetypal MPDs had lower symptom severity than their unmedicated counterparts; whereas medicated and unmedicated Atypical MPDs had no differences in symptom scores. Our findings suggest that frontal versus posterior functional imbalance as measured by ALFF is a novel putative trans-diagnostic biomarker differentiating subtypes of MPDs that could have implications for precision medicine.

Genomics at cellular resolution: insights into cognitive disorders and their evolution.

High-throughput genomic sequencing approaches have held the promise of understanding and ultimately leading to treatments for cognitive disorders such as autism spectrum disorders, schizophrenia and Alzheimer's disease. Although significant progress has been made into identifying genetic variants associated with these diseases, these studies have also uncovered that these disorders are mostly genetically complex and thus challenging to model in non-human systems. Improvements in such models might benefit from understanding the evolution of the human genome and how such modifications have affected brain development and function. The intersection of genome-wide variant information with cell-type-specific expression and epigenetic information will further assist in resolving the contribution of particular cell types in evolution or disease. For example, the role of non-neuronal cells in brain evolution and cognitive disorders has gone mostly underappreciated until the recent availability of single-cell transcriptomic approaches. In this review, we discuss recent studies that carry out cell-type-specific assessments of gene expression in brain tissue across primates and between healthy and disease populations. The emerging results from these studies are beginning to elucidate how specific cell types in the evolved human brain are contributing to cognitive disorders.

SUN-254 Angiotensin II Stimulates Microglia Cell Inflammatory Responses

Angiotensin II (AngII) is the principal effector molecule of the renin-angiotensin system (RAS). It’s effects on the cardiovascular and renal system are well-documented. AngII acts mainly via interaction with the AngII type-1 receptor (AT1R). Disordered levels of AngII lead to hypertension and cardiovascular disease. Increasing evidence suggests that AngII may also play a role in the pathophysiology of neurodegenerative diseases through unclear mechanisms. We investigated AngII, AT1R and AT2R levels in a mouse model of neurodegenerative disease, the experimentally induced autoimmune encephalomyelitis (EAE) mouse. In EAE mice, AngII and AT1R gene expression in brain tissue were significantly increased when compared to control mice (3.2 folds ±1.9, p<0.05, n=5; and 2.6 folds ±1.1, p<0.01, n=5 respectively). In addition, iNOS mRNA expression by qRT-PCR was likewise upregulated in EAE mice compared to control (3.4 ± 1.4 folds, p<0.01, n=5). We then studied the effects of AngII in human microglial cells (HMC3) -resident innate immune cells of the central nervous system (CNS). In HMC3 cells, treatment with AngII up-regulated the expression IL-6 (3.9 folds ± 1.2, p<0.01, n=4) and increased IL-6 concentration by 83% (p<0.05, n=4) by ELISA; effects that were blocked by the AT1R antagonist, Losartan. Also, AngII induced TNF-α production, increasing its concentration by 90% (p<0.05, n=4), an increase that was blocked by Losartan. We also quantified Nitric Oxide (NO) production by using Griess Reagent and reactive oxygen species (ROS) production by the MUSE Oxidative Stress assay. In these cells, NO and ROS production were significantly increased by AngII (p<0.05, n=4) and treatment with Losartan reduced their production (p<0.05, n=4). In addition, AngII treatment induced iNOS overexpression (2.5 folds ±0.8, p<0.05, n=4); results that are consistent with increases in the EAE mice. These data suggest that AngII can activate microglia cell inflammatory responses and as such may contribute to the pathophysiology of CNS inflammation and neurodegenerative diseases.

Genetic meta-analysis of obsessive-compulsive disorder and self-report compulsive symptoms.

We investigated whether obsessive–compulsive (OC) symptoms from a population‐based sample could be analyzed to detect genetic variants influencing obsessive–compulsive disorder (OCD). We performed a genome‐wide association studies (GWAS) on the obsession (rumination and impulsions) and compulsion (checking, washing, and ordering/precision) subscales of an abbreviated version of the Padua Inventory (N = 8,267 with genome‐wide genotyping and phenotyping). The compulsion subscale showed a substantial and significant positive genetic correlation with an OCD case–control GWAS (r G = 0.61, p = .017) previously published by the Psychiatric Genomics Consortium (PGC‐OCD). The obsession subscale and the total Padua score showed no significant genetic correlations (r G = −0.02 and r G = 0.42, respectively). A meta‐analysis of the compulsive symptoms GWAS with the PGC‐OCD revealed no genome‐wide significant Single‐Nucleotide Polymorphisms (SNPs combined N = 17,992, indicating that the power is still low for individual SNP effects). A gene‐based association analysis, however, yielded two novel genes (WDR7 and ADCK1). The top 250 genes in the gene‐based test also showed a significant increase in enrichment for psychiatric and brain‐expressed genes. S‐Predixcan testing showed that for genes expressed in hippocampus, amygdala, and caudate nucleus significance increased in the meta‐analysis with compulsive symptoms compared to the original PGC‐OCD GWAS. Thus, the inclusion of dimensional symptom data in genome‐wide association on clinical case–control GWAS of OCD may be useful to find genes for OCD if the data are based on quantitative indices of compulsive behavior. SNP‐level power increases were limited, but aggregate, gene‐level analyses showed increased enrichment for brain‐expressed genes related to psychiatric disorders, and increased association with gene expression in brain tissues with known emotional, reward processing, memory, and fear‐formation functions.