DNA methylation of gene promoter regions represses transcription and is a mechanism via which environmental risk factors could affect cells during development in individuals at risk for schizophrenia. We investigated DNA methylation in patient-derived cells that might shed light on early development in schizophrenia. Induced pluripotent stem cells may reflect a “ground state” upon which developmental and environmental influences would be minimal. Olfactory neurosphere-derived cells are an adult-derived neuro-ectodermal stem cell modified by developmental and environmental influences. Fibroblasts provide a non-neural control for life-long developmental and environmental influences. Genome-wide profiling of DNA methylation and gene expression was done in these three cell types from the same individuals. All cell types had distinct, statistically significant schizophrenia-associated differences in DNA methylation and linked gene expression, with Gene Ontology analysis showing that the differentially affected genes clustered in networks associated with cell growth, proliferation, and movement, functions known to be affected in schizophrenia patient-derived cells. Only five gene loci were differentially methylated in all three cell types. Understanding the role of epigenetics in cell function in the brain in schizophrenia is likely to be complicated by similar cell type differences in intrinsic and environmentally induced epigenetic regulation. Schizophrenia-associated differences in the DNA methylation status of patient-derived cells suggest it could affect early brain development. Mechanisms that control gene expression without altering the genetic code, such as DNA methylation, could explain how environmental risk factors contribute to schizophrenia in genetically susceptible individuals. Alan Mackay-Sim and colleagues from Griffith University, Australia, carried out genome-wide comparisons of DNA methylation in induced pluripotent stem (iPS) cells, olfactory neurosphere-derived cells and fibroblasts from patients and controls. Differences in the DNA methylation pattern between patient and control iPS cells, which could reflect what happens in the embryo, suggest a disease-associated effect very early on in development. Only five genes were differentially methylated in all three patient-derived cell types compared to controls. None of these genes has previously been associated with schizophrenia and may represent new targets for future research. From a neurobiological perspective, environmental factors must act ultimately on cells in the nervous system to change the way they act, or interact, in the neuronal networks that determine behavior. This may occur through epigenetic mechanisms that alter gene expression without affecting the genetic code via modifications of DNA and DNA-associated histone proteins by acetylation, phosphorylation, and methylation.3 Even the social environment can act epigenetically: maternal grooming of rat pups reduced DNA methylation of the glucocorticoid receptor gene promoter in the hippocampus, increasing transcription factor binding, and reducing the hypothalamic-pituitary-adrenal stress response in adulthood.4 Such observations have helped shape the view that epigenetics is a potential “non-genetic” factor leading to both causes and effects in neuropsychiatric disorders.6 Thus, the “biological” environment during development in utero or following birth, such as prenatal infections7 and vitamin D status,8 as well as the “social” environment, such as migrant status9 and childhood trauma,10 might act on the brain via epigenetic mechanisms to alter gene expression, brain development, and ultimately behavior, leading to schizophrenia in genetically susceptible individuals.11Schizophrenia is recognized as a polygenic disorder with the contribution of potentially hundreds of risk genes that affect brain development.13 and in leukocytes.14 One aim of this study was to determine whether there is any schizophrenia-associated DNA methylation in patient-derived induced pluripotent stem (iPS) cells that could indicate the influence of genetic risk factors very early in development. Olfactory neurosphere-derived (ONS) cells and fibroblasts provide contrast between schizophrenia-associated DNA methylation in adult cells from neural and non-neural origins. A second aim was to determine whether schizophrenia involves DNA methylation that is carried into adulthood, exemplified by patient-derived ONS cells and fibroblasts. DNA methylation regulates gene expression, so it was also of interest to explore mRNA expression profiles in the three cell types. The final aim of this study was to identify which cell functions would be affected by schizophrenia-associated differences in DNA methylation and gene expression. These aims were achieved by obtaining genome-wide DNA methylation and gene expression profiles from iPS cells, ONS cells, and fibroblasts from the same patients, and controls were obtained and the schizophrenia-associated genes were subjected to functional annotation and pathway analysis to identify affected cell functions and processes.The majority of studies of epigenetic modifications in schizophrenia are DNA methylation analyses targeted to specific genomic regions of candidate genes , from the non-pluripotent cell types  Correction for multiple testing]. There were 7,854 CpG loci that were differentially methylated among the three cell types, 28% of the total detected probes on the array, while the majority of detected gene loci (69%) were methylated similarly in all cells, independently of cell type or disease status. The significant CpG loci were used as input to an unsupervised hierarchical cluster analysis, which identified three main clusters that distinguished between the different cell types . This analysis revealed 8231 genes/probes that were differentially expressed among the three cell types, 41% of the probes detected on the array . These significant probes were used as input to an unsupervised hierarchical cluster analysis, which identified three main clusters that distinguished between the different cell types  from the non-pluripotent cell types , in ONS cells there were 1328 CpG loci . Gene loci that were significantly hypomethylated in all patient cell types compared to control cells were PSMD5, LRRN4/C20orf75, FAM20B, and AEN/ISG20L1. One gene locus was significantly hypermethylated in patient cells (ID2).A small number of probes on the array were differentially methylated among cell lines derived from schizophrenia patients and controls. These represented 3–5% of the probes depending on the cell type: in iPS cells there were 883 CpG loci with statistically significant patient-control differences . Several GO categories were identified in all cell types: “cellular growth and proliferation”, “cell death and survival”, “carbohydrate metabolism” and “cellular movement”. Although the defined GO categories were similar among the cell types, the schizophrenia-associated differences are composed of different individual genes that assemble into different functions within each GO category (Table P < 0.05).The CpG loci that were differentially methylated in patient-derived and control-derived cells were subject to Gene Ontology (GO) analysis. GO categories and functional annotations within the categories, are shown in Table ry Table . Pathwayp < 0.05, with Benjamini and Hochberg FDR correction for multiple testing). Differentially expressed genes in the ONS cells and fibroblasts were identified by reanalysis of our previous data15 using the same statistical criteria as used for iPS cells. The differentially expressed genes in iPS, ONS cells and fibroblasts were then subject to GO analysis. In iPS cells there were four GO categories made up of 13 functional annotations that were significantly different between patient-derived and control-derived iPS cells . Differentially expressed genes were identified using the same analysis protocols and were then subject to GO analysis  and several others shared by two of the three cell types and neurons (Supplementary Table P < 0.05).We reanalyzed published transcriptome data from iPS-derived neurons generated from patients and controls.purple and pink labels, Figs. yellow labels, Figs. purple labels), whereas genes whose expression was decreased (blue labels) were interconnected with hypermethylated genes (pink labels).We looked for a relationship between the differentially DNA methylated loci and the differentially expressed genes in the GO category “cell movement”, which was common to iPS cells and ONS cells for DNA methylation and gene expression. Ingenuity pathway analysis (IPA) was used to construct networks of the differentially methylated and differentially expressed genes in iPS cells and ONS cells. Genes were included if they had direct interactions. Coordination between DNA methylation and gene expression was noted: hypomethylated loci associated with increased gene expression and hypermethylated loci associated with decreased gene expression. In iPS cells, the 49 differentially expressed genes  and fibroblasts  but not the iPS cells . The differentially expressed genes in iPS cells and ONS cells were significantly associated with the SZ-PPI network  but not the fibroblasts .In order to evaluate either cell-specific DNA methylation or gene expression profiles were associated with schizophrenia risk functional pathways, we used a SZ-PPI network that was built from genes representing confident loci identified by genome-wide association studies,ID2 is highly expressed in the cortex with peak expression during the early prenatal period (8–9 weeks post conception) decreasing at later periods. PSMD5, AEN, and FAM20B are similar in their developmental patterns of expression from the earliest stage of development (4–7 weeks post conception) after which expression in the cortex does not vary much throughout development. During late infancy there is a transient drop in expression in hippocampus and striatum with cortical expression maintained through to adulthood. LRRN4 is virtually absent from the cortex and hippocampus; its highest expression is seen in the striatum from late childhood through to adulthood.All five of the differentially methylated genes in the three different schizophrenia-derived cells are expressed in the human brain during development and into adulthood Fig. . TemporaPSMD5, AEN, FAM20B, LRRN4) and one hypermethylated gene (ID2). PSMD5, AEN and FAM20B shows moderate levels of mRNA expression throughout the cortex at all ages starting very early in development. Hypomethylation would be predicted to enhance these expression levels as observed for PSMD5, whose expression is significantly increased in the frontal cortex in postmortem brain in schizophrenia.19LRRN4 expression is absent from the cortex, but is expressed in the striatum in later stages of development and into adulthood. None of these genes has been previously linked to schizophrenia. PSMD5 inhibits the proteasome after induction by NFκB;20LRRN4 is a transmembrane adhesion protein involved in neurite growth;21FAM20B is a Golgi-located kinase that regulates the number of glycosaminoglycan chains in proteoglycans;22 and AEN is an endonuclease controlling autophagy, whose transcription is regulated by the p53 family of genes.23ID2 mRNA is expressed at very high levels during early prenatal stages after which its expression decreases with age. Hypermethylation of ID2 would be predicted to blunt this early peak of expression. ID2 is expressed in neuroblasts and some neurons during embryogenesis24 and enhances cell proliferation and regulates axonal growth.25 Although these gene loci were methylated in the same way in all three cell types, it is too early to say whether they might be carried as heritable signals. In general though, the lack of overlap among the cell types in schizophrenia-associated DNA methylation suggests that most may be too labile to convey a heritable signal.5 These spatial and temporal patterns of gene expression in the developing cortex, combined with schizophrenia-associated DNA methylation, make these genes interesting targets for future research on the neurodevelopmental origins of schizophrenia.Our experiments show that DNA methylation in patient iPS cells is different from control cells. If iPS cells reflect what happens in the embryo, then schizophrenia risk genes may be acting very early in development. The results also show that schizophrenia-associated DNA methylation in iPS cells is not shared by adult cells (ONS cells and fibroblasts) from the same individuals, except for five gene loci that were differentially methylated in all three cell types in patient cells compared to control cells: four hypomethylated genes  even though the genes contributing to these functions were different and largely unique for each cell type. “Cellular Movement” is particularly interesting because cell migration is dysregulated in patient-derived ONS cells compared to control-derived cells.27 Three of the genes with shared DNA methylation status could affect adhesion and motility: LRRN4 and ID2 are involved with NOGO cell adhesion receptor signaling25 and FAM20B is involved in cell adhesion by regulating proteoglycan composition.22 Cell movement was also impaired in patient-derived B lymphoblasts compared to controls.28 Dysregulated cell motility and migration may be a general property of cells derived from schizophrenia patients as many schizophrenia risk genes are over-represented in pathways controlling neuronal migration and cell adhesion.31 Altered cell migration is a plausible risk for altering neurodevelopmental trajectories in schizophrenia.33As a way of assessing the link between genetic risk for schizophrenia and DNA methylation we tested the differentially methylated genes for their association with the SZ-PPI network, which is based on schizophrenia risk genes from genome-wide association studies.34 Similarly, pathway analysis of DNA methylation in blood from twins discordant for schizophrenia identified differentially methylated genes associated with “hematological system development and function”.35 Taken together with our observations, it seems reasonable to conclude that schizophrenia-associated DNA methylation and downstream gene expression are dominated by the cell type and its functional demands.DNA methylation analysis of blood DNA from 98 patients with schizophrenia and 102 controls revealed 16 CpG loci that were significantly associated with schizophrenia with the inflammatory response as the most significant biological function affected in the patient-derived DNA.36This study provides a genome-wide view of schizophrenia-associated DNA methylation (and gene expression) of three cell types: iPS cells, in which the reprogramming process erases and rewrites the epigenome, and ONS cells and fibroblasts, which may carry epigenetic marks from the adults from which they derive. The epigenetic marks on different cell types from the same individuals show that schizophrenia status affects each cell type differently. How this would be reflected in the developing brain remains to be explored and the effect of schizophrenia-associated DNA methylation on neurons and glia is unknown. Additionally, there are other epigenetic mechanisms that may contribute. For example, histone methylation in patient-derived primary olfactory cells identified schizophrenia-associated histone methylation affecting 22 genes that contribute to cell functions different from those identified here.15All patients were medicated with antipsychotic drugs and all smoked cigarettes at the time of biopsy, whereas none of the controls did. The medications and doses differed among the patients. All cells were cultured for more than 4 weeks, so any direct drug effects would be eliminated, but it is possible that medication and smoking prior to tissue biopsy of nose and skin could lead to schizophrenia-associated DNA methylation. This seems unlikely given the small overlap among the cell types, assuming that medication-induced or smoking-induced DNA methylation would likely be targeted to specific genes. In previous analyses of the same ONS cells and fibroblasts we found no patient-control differences in gene expression or cell functions that can be ascribed to medication or smoking.37 The small number of individuals limits the statistical power of the study, leading to underestimation of the number of schizophrenia-associated DNA methylated loci at the expense of the reduction in false positives. It can be expected that more loci will emerge as larger samples are examined. These statistical limitations are in common with other patient-derived iPS cell studies because the difficulties of iPS cell generation and maintenance impart restraints on the number of cell lines that are feasible to generate and experiment upon.37Our findings should be considered preliminary, being based on only a small number of individuals. While each is represented by three cell types, these relatively small numbers make the results open to selection bias and individuals were not represented equally in the numbers of cell lines because of technical difficulties. Small sample sizes obscure group differences because of individual variability among the patients and controls. Variability was minimized where possible by using standardized culture protocols, and the iPS cells were selected for homogeneity using the pluripotency marker, SSEA4.39 Demographic details of the individuals and details of the cell lines derived from them are in Table 37The patients and controls from whom the cells were derived are a subset of a cohort of 18 donors from whom ONS cell gene expression and cell functions are previously described.2.15 At each passage, and for DNA and mRNA extraction, the cells were dissociated with trypsin. Established iPSC lines37 were grown on a monolayer of mouse embryonic fibroblasts . The culture medium consisted of DMEM-F12 with: 20% Knockout Serum Replacement, 2 mM GlutaMAX-1, 1× Non-Essential Amino Acids, 0.1 mM β-mercaptoethanol, 1× penicillin/streptomycin , and 50 ng/ml basic fibroblast growth factor . Cell lines were passaged mechanically. The cell lines were characterized previously and shown to be pluripotent.37 A human embryonic stem cell line (HES3) was used as a comparator control. For the DNA methylation and gene expression analyses, the pluripotent fractions of the iPS cells and HES3 cell cultures were selected by flow cytometry using the cell surface marker, SSEA4. The cultures were harvested using collagenase IV, washed in DMEM-F12 and immunostained with SSEA4 , and then sorted using flow cytometry . This sorted SSEA4 fraction was used for subsequent DNA and RNA isolation and analysis. The cells used here are available from the Griffith Institute for Drug Discovery, Griffith University, Australia (http://www.griffith.edu.au/), subject to patient consent, an appropriate material transfer agreement, and payment of shipping and handling fees.Aliquots of established ONS cells and fibroblasts frozen in liquid nitrogen were thawed and grown under standard conditions on tissue culture plastic in Dulbecco’s Minimum Essential Medium with F12  supplemented with 10% fetal bovine serum (Gibco BRL) at 37 °C and 5% CO® Genomic DNA Purification Kit (Promega) according to the manufacturer’s protocol. DNA quantity and quality were determined using Quant-iT™ PicoGreen® dsDNA Kits (Invitrogen). Sodium bisulfite conversion of 500 ng genomic DNA was performed with an EZ DNA Methylation Kit (Zymo Research), with the alternative incubation conditions recommended for Illumina Infinium® Methylation Assay. After conversion, DNA quantity was measured using a NanoDrop spectrophotometer set at ssDNA and percentage recovery calculated.Genomic DNA was extracted from several passages from each cell line with a Wizardβ-values: methylated intensity divided by the sum of methylated and unmethylated intensity. For general assessment of the methylation state of each cell type, probes were binned into three categories: hypermethylated ≥70%, hypomethylated ≤30%, mid-methylated 30–70%. The β-value was used for initial clustering because it is biologically more intuitive; however, it is severely limited for statistical analysis because of heteroscedasticity outside the middle range.40 For all statistical comparisons the fluorescence intensities were converted to M-value using the lumi package in R. Methylation data were deposited into ArrayExpress (Accession Number E-MTAB-5016).Methylation profiles were generated with the Infinium HumanMethylation27 BeadChip Kit , according to the manufacturer’s protocol. Raw data were imported in GenomeStudio, with which the fluorescence intensity of each probe was extracted and used to generate 37 The gene expression data comparing the three cell types are deposited into ArrayExpress (Accession Number E-TABM-5016). For comparison of gene expression in the three cell types the same iPS cell gene expression data were used, while the ONS cell and fibroblast gene expression was from the larger data set that included the same individuals,15 available at ArrayExpress accession number E-TABM-724.RNA was extracted from cell lysates using the RNeasy Micro Kit (Qiagen) according to the manufacturer’s protocol. For comparison of gene expression and DNA methylation in the cells from the same individuals the gene expression profiles of the selected iPS cells, ONS cells, and fibroblasts were analyzed using lumi and limma packages in R/BioConductor.http://www.brainspan.org).41 This is a database of RNA expression (RNA-seq) of about 52,400 genes in multiple brain regions generated from 579 tissue samples from 41 developing and adult postmortem brains’ early prenatal development to adulthood, divided into 13 developmental stages: embryonic [4–7 post-conceptional weeks (pcw)]; early prenatal A (8–9 pcw); early prenatal B (10–12 pcw); early mid-prenatal A (13–15 pcw); early mid-prenatal B (16–18 pcw); late mid-prenatal (19–24 pcw); late prenatal (25–38 pcw); early infancy (birth to 5 months); late infancy (6–18 months); early childhood (19 months to 5 years); late childhood (6–11 years); adolescence (12–19 years); adulthood (20–60+years). In the present study, the cortical region data were grouped into Prefrontal cortex, including ventrolateral prefrontal cortex, orbitofrontal cortex, medial prefrontal cortex (anterior cingulate), and dorsolateral prefrontal cortex; primary sensory cortex, including primary motor cortex , primary auditory cortex, primary visual cortex , and primary somatosensory cortex ; temporal cortex, including posterior superior temporal cortex (area 22c) and inferolateral temporal cortex (area 20). Subcortical regions chosen were the striatum and hippocampus. Brainspan provides quantitative data based on RNA-seq expression in the commonly used units of RPKM (reads per kilobase of exon model per million mapped reads). For details see the “Technical White Paper: Transcriptome profiling by RNA sequencing and Exon Microarray” (available at http://www.brainspan.org).We identified five genes whose DNA methylation in all three patient cell types was different from controls. The expression of these genes was investigated in the developing human brain using available RNA sequencing data from BrainSpan database (r2) between replicates were very high . PCA provided an unbiased method to determine whether the cell types could be distinguished from each other. Cell-type differences in gene expression and methylation were determined with limma package in R. For the analysis, the consecutive passages were treated as technical replicates and accounted for in the linear model. The iPS cell line clones of each patient were treated as biological replicates. All p-values were adjusted for multiple testing using the Benjamini and Hochberg procedure for FDR correction. The differentially methylated and differentially expressed genes were then subjected to cluster analysis using Cluster 3.042 and visualized in Java Treeview.43DNA methylation and gene expression profiles for each control-derived cell type  and the ES cells were subjected to principal components analysis (PCA) (princomp package in R) using all the probes detected on each array. To eliminate cell culture artefacts and technical errors affecting methylation status, all samples were measured in triplicate. PCA identified one outlier clustering separately: GU9569fb-cont P6  and interactions between them . Edges between differentially methylated genes and differentially expressed genes were only considered if there was evidence of activation (hypomethylation of CpG loci leading to up-regulated gene expression) or inhibition (hyper-methylation of CpG loci leading to down-regulated gene expression).Using IPA 8.5 , the differentially methylated and expressed genes were subjected to GO over-representation analysis,18 built from ‘seed’ genes and their first-degree interacting neighbors based on high confidence loci identified in previous genome-wide association studies obtained from the schizophrenia gene resource.17 The standardized Z-score was estimated using a binomial distribution with a one-tailed Z-test (Eq. P < 0.05 with critical Z-score of 1.65.O = observed number of gene variants in the SZ-PPI network, E = expected number of gene variants in the SZ-PPI network, N = total number of gene variants, p = expected frequency of gene variants, q = 1−pThe methylome and transcriptome data from iPS cells, ONS cells, and fibroblasts were compared to a SZ-PPI networkSupplementary Table 1Supplementary Figure 1Supplementary Table 2Supplementary Table 3Supplementary Table 4Supplementary Table 5


Gpr88−/− mice fed either standard chow or high fat diet (HFD). Gpr88−/− mice showed significantly reduced adiposity accompanied with suppressed spontaneous food intake, particularly pronounced under HFD treatment. While energy expenditure was likewise lower in Gpr88−/− mice, body weight gain remained unchanged. Furthermore, deregulation in glucose tolerance and insulin responsiveness in response to HFD was attenuated in Gpr88−/− mice. On the molecular level, distinct changes in the hypothalamic mRNA levels of cocaine-and amphetamine-regulated transcript (Cartpt), a neuropeptide involved in the control of feeding and reward, were observed in Gpr88−/− mice. In addition, GPR88 deficiency was associated with altered expressions of the anorectic Pomc and the orexigenic Npy in the arcuate nucleus, especially under HFD condition. Together, our results indicate that GPR88 signalling is not only important for reward processes, but also plays a role in the central regulatory circuits for energy homeostasis.GPR88 is an orphan G-protein-coupled receptor with predominant expression in reward-related areas in the brain. While the lack of GPR88 has been demonstrated to induce behavioral deficits, the potential function of the receptor in the control of food intake and energy balance remains unexplored. In this work, the role of GPR88 in energy homeostasis was investigated in  Current pharmacological treatments for obesity, which primarily aim to suppress energy intake through reducing appetite or dietary fat absorption2, have demonstrated limited effectiveness and efficacy3 and can also lead to complex side effects4. The discovery of novel and effective pharmacotherapeutic targets is therefore a high priority.Obesity occurs when chronic increase in energy intake significantly exceeds energy expenditure6. Due to the fact that GPCRs are responding to various extracellular signals and thereby modulating diverse physiological processes6, more than 40% of clinically approved drugs target GPCRs to modulate their effects8. Despite rapid research progress that led to the deorphanization of more than 300 GPCRs in the past two decades, over 150 GPCRs still remain orphans10, among which a number were indicated as regulators of energy metabolism12, hence offering therapeutic promises for obesity.G-protein-coupled receptors (GPCRs) represent the largest membrane receptor family in the mammalian genome, with over 800 genes identified in humans16. Associated with the reward network in the striatum, GPR88 has been implicated in numerous behaviors linked to neurological conditions in both rodents and humans, namely bipolar disorders, schizophrenia19, responses to psychostimulant drugs20 and antidepressants22, as well as learning and social behavior24. In addition to the abundant distribution throughout the striatum including the nucleus accumbens (Acb), caudate putamen (CPu) and olfactory tubercle, GPR88 expression is also enriched in inferior olive in the brainstem, cortex and amygdala26, with minimal to absent expression in peripheral tissues27. Interestingly, many of the GPR88-rich areas are involved in the reward processing system that is integrated and interrelated with the circuits controlling energy balance to direct downstream effects on appetite and food intake29. The functional implication with the anatomical distribution of GPR88 expression suggests a potential role of the receptor in regulating energy homeostasis, an underexplored area of GPR88 research.One of these orphan GPCR candidates is GPR88. This receptor is predominantly expressed in striatal projection neurons, with high evolutionary conservation between humans and rodents in both primary structure and expression pattern, suggesting critical functional conservationGpr88 globally showed over-represented striatal mRNAs that encoded proteins involved in cell response to nutrient levels and starvation, as revealed by microarray combined with gene ontology analysis16. In the same study, the most upregulated gene in the striatum of Gpr88 knockout mice compared with controls was the cocaine- and amphetamine-regulated transcript (Cartpt)16, a key neuropeptide central to the control of appetite and energy balance30. Strikingly, microarray profiling in our Cartpt knockout mouse model31 revealed that Gpr88 was amongst the most significantly upregulated GPCR mRNAs in the hypothalamus compared to wild-type mice, despite moderate hypothalamic expression of the receptor25. These correlative findings in the two genetic models indicate a potential function for GPR88 in the energy homeostatic circuit. Furthermore, plausible involvement of GPR88 in energy metabolism was denoted in an investigation of the sensitivity of individual abdominal white adipose depots to ghrelin exposure32, a gastric hormone that stimulates orexigenic hypothalamic neurons and plays a critical regulatory role in lipid storage and distribution34. In contrast with earlier studies reporting the absence or minimal expression of Gpr88 in peripheral tissues in rodents27, Gpr88 mRNA was identified to be more highly expressed in the ghrelin-unresponsive epididymal fat than the ghrelin-responsive retroperitoneal adipose tissue in rats32. The depot-specific Gpr88 expression may attribute to differential energy utilization and lipid handling mechanisms32 involving this receptor. Concordantly, in a separate microarray study, Gpr88 mRNA was upregulated in the hypothalamus following cold exposure in both leptin-deficient and wild-type mice35. The leptin-independent alteration in expression regardless of the nutritional status indicated possible association of GPR88 with the mobilization of fuel reserves in cold-activated thermogenesis35.The emerging potential of GPR88 in energy homeostatic regulation is supported by several lines of evidence. First, mice lacking Gpr88 knockout mouse model. As previous characterizations of GPR88-deficient models focused mainly on behavioral parameters and psychiatric contexts37, the present work offers the first insights into the physiological roles of this receptor in energy homeostatic control. The metabolic phenotypes as well as the underlying mechanisms were investigated. Effects of high fat diets on the manifestation of GPR88 deficiency were also addressed in comparison with standard chow feeds to examine the potential influence of Gpr88 deletion on diet-induced obesity.In this study, we aimed to elucidate the detailed function of GPR88 in the regulation of energy balance employing a germline Gpr88−/− mice were born at the expected Mendelian ratios with equal gender ratio and litter size as controls (data not shown). In agreement with recent studies23, no significant differences in body weight or appearance were observed at birth between these mice and their control littermates (data not shown). Both male and female mice were studied under chow conditions, while only male mice were subjected to HFD treatment. Based on the data from extensive metabolic characterization, male and female mice demonstrated consistency for the majority of the phenotypic traits, with greater prominence in phenotypes in males. Hence, data for male mice are the main focus, while key data for female mice are included as supplementary figures. In order to study the baseline metabolic characteristics of this Gpr88−/− model, and the effects of high fat dietary intervention, we first measured body weight (BW) gain and body composition under standard chow diet as well as HFD conditions.Gpr88−/− mice on both chow and HFD gained similar body weight to WT control mice when expressed in absolute value as well as a percentage of initial body weight  were a generous gift from Prof. Richard Palmiter , with targeting strategies described in detail previously16. All mice were housed under conditions of controlled temperature of 22 °C and illumination . Mice were provided with ad libitum access to water and either standard chow diet /g; Gordon’s Specialty Stock Feeds, Yanderra, NSW, Australia) or high fat diet  according to grouping. Both male and female mice were used for all experiments under chow conditions, whereas only male mice were subjected to HFD treatment.All research and animal care procedures were approved by the Garvan Institute/St. Vincent’s Hospital Animal Ethics Committee and were in agreement with the Australian Code of Practice for the Care and Use of Animals for Scientific Purposes. The Gpr88 knockout 16 and wild-type (WT) groups were subjected to HFD feeding for 10 wk until sacrifice at 18 wk of age. The remaining subsets of mice continued on the standard chow diet. The same experimental procedures were performed on both chow- and HFD-fed groups in an age-matched manner.All mice were initially fed a standard laboratory chow diet. At 8 weeks (wks) of age, subsets of mice from both the Gpr88−/− and WT mice fed on standard chow diet or HFD were subject to the same experimental procedures as follows. Body weight was measured weekly throughout the duration of studies. Mice were assessed for spontaneous/basal food intake in the fed state as well as for fasting-induced food intake in response to 24-hr fasting at 12 wks of age. In brief, mice were transferred from group housing on soft bedding to individual cages with paper towel bedding for 3 nights of acclimatization. Basal daily food intake was determined as the average of duplicate readings obtained over two consecutive 24-hr periods. Twenty four-hr fasting-induced food intake was subsequently measured at 1, 3, 7, and 24 hr after refeeding with the respective types of diet, while the corresponding body weight was recorded in parallel.All ad libitum access to water and food of respective diet types. Body weight was measured and food given in excess was weighed before and after the recording period for the quantification of daily food intake after subtraction of spillage. Oxygen consumption (VO2) and carbon dioxide production (VCO2) were measured every 27 min. The respiratory exchange ratio (RER) was calculated as the quotient of VCO2/VO2, with 100% carbohydrate oxidation represented by the value of 1.0 and 100% fat oxidation the value of 0.7. Energy expenditure  was determined as calorific value (CV) x VO2, where CV is 3.815 + 1.232 x RER. Data obtained for the 24-hr monitoring period were averaged at 1-hr intervals for energy expenditure and RER.All mice from both chow- and HFD-fed groups were evaluated for metabolic parameters and physical activity at 16 wk of age. For energy metabolism, metabolic rate was measured by indirect calorimetry using an 8-chamber open-circuit calorimeter . Mice were housed individually in specially built Plexiglas cages (20.1 × 10.1 × 12.7 cm). Temperature was maintained at 22 °C with airflow of 0.6 L/min. Mice were singly housed for 3 days in home cages prior to acclimatization in Plexiglas cages for 24 hr before commencement of recording. Monitoring was subsequently performed for 24 hr in the metabolic chambers. Mice were provided with All mice from both chow- and HFD-fed groups were subjected to an initial body composition analysis using the dual-energy X-ray absorptiometry  system at 10 wk of age. A second DXA scan was performed 6 wk after initial DXA measurements at 16 wk of age, immediately following completion of the indirect calorimetry assessment of energy metabolism and physical activity. Animals were anesthetized with isoflurane for the scanning procedure to determine whole body bone mineral density (BMD), bone mineral content (BMC), fat and lean mass, where lean mass corresponds to non-fat and non-bone tissue content. The head of the animal was excluded while the tail included for the analysis.All mice from both chow- and HFD-fed cohorts were examined by intraperitoneal glucose tolerance test (IPGTT) and insulin tolerance test (IPITT). IPGTT and IPITT were conducted at 14 and 17 wk of age respectively. For IPGTT, mice were subjected to 6-hr fasting where food was removed from cage hoppers at 09:00 hr and injection of a dose of a 10% D-glucose solution  was performed 6 hr later into the peritoneal cavity. For IPITT, mice were subjected to 5-hr fasting where food was removed from cage hoppers at 10:00 hr and injection of a dose of insulin (0.5 IU/kg body weight)  was performed 5 hr later into the peritoneal cavity. For both tests, tail vein blood was collected at 0, 15, 30, 60, 90 min following glucose or insulin injection and glucose concentrations were measured using a glucometer . For IPGTT, insulin levels were subsequently quantified using a sensitive rat insulin radioimmunoassay (RIA) kit . Glucose and insulin tolerance curves constructed for the glucose levels obtained during IPGTT and IPITT respectively are presented in terms of absolute values. Area under the glucose (AUCglucose) or insulin (AUCinsulin) concentration curves between 0 and 90 min after glucose injection during IPGTT were plotted after subtraction of the initial concentrations prior to injection.Following completion of studies, all mice from both chow- and HFD-fed groups were sacrificed at 18 wk of age. Animals were culled between 13:00 to 17:00 hr through cervical dislocation followed by decapitation. Brains were promptly collected and frozen on dry ice, then stored at −80 °C until subsequent analysis as described below. The white adipose tissue (WAT) depots from the inguinal, epididymal or periovarian , retroperitoneal and mesenteric regions were removed and weighed. Tissue weights are normalized and expressed as a percentage of body weight.In situ hybridization was conducted on brain sections of WT (n ≥ 7) and Gpr88−/− (n ≥ 5) mice from chow- and HFD-fed groups to determine mRNA expression of Cartpt, proopiomelanocortin (Pomc) and neuropeptide Y (Npy) at the hypothalamus following procedures as previously described62. Briefly, matching coronal brain sections (25 µm) collected from the WT and Gpr88−/−mice were prepared from specific brain levels with respect to the bregma to represent the hypothalamic areas involved in the regulation of energy homeostasis. Brain sections from mice of both genotypes and diet groups were processed in parallel for quantitative comparison. Detection of the mRNA expression was performed for Cartpt, Npy, and Pomc in the arcuate nucleus (Arc), as well as Cartpt in the dorsomedial hypothalamic nucleus (DMH) and lateral hypothalamic area (LHA). The cryosections were hybridized with [α-35S]-thio-dATP  radiolabelled DNA oligonucleotides complementary to mouse Cartpt (5′-TCCTTCTCGTGGGACGCATCATCCACGGCAGAGTA GATGTCCAGG-3′), Npy (5′-GAGGGTCAGTCCACACAGCCCCATTCGCTTG TTACCTAGCAT-3′), and Pomc (5′-TGGCTGCTCTCCAGGCACCAGC TCCACACATCTATGGA-GG-3′). Hybridization signals on sections were visualized by exposure to BioMax MR film  for 7–10 days and digitalized images from the scanned autoradiograms were acquired. For structural details, the brain sections were photoemulsion-dipped and superficially counterstained with haematoxylin, with which regions of interest were visualized and captured into digital images acquired by bright-field microscopy. Quantification of the mRNA expression levels of respective genes was performed by measuring the relative optical densities (RODs) within the brain areas of interest outlined with consistent defined dimensions across corresponding sections on the photomicrographs using the National Institutes of Health ImageJ 1.61 software . Background labelling was considered uniform with signal levels below 5% of specific signal levels and was subtracted from the resultant signal density. Data are evaluated and presented as percentage of ROD averaged from at least three sections per mRNA assessed per animal.p-value ≤ 0.05.All data are presented as means ± SEM. Differences amongst mouse groups of various genotypes and dietary treatments were assessed by ANOVA or repeated-measures ANOVA combined with Bonferroni post-hoc analysis where appropriate. Energy expenditure, RER and physical activity over the continuous 24-hr period were averaged for the whole 24-hr period, as well as the 12-hr light and dark phases individually. Comparison of energy expenditure  between groups was performed by the analysis of covariance (ANCOVA) with lean mass as the covariate. The adjusted means of energy expenditure at a common lean mass for the comparison were generated by ANCOVA as presented. Statistical analyses were performed with GraphPad Prism 6 for Mac OS X  and SPSS for Mac OS X version 16.0.1 . Statistical significance was defined as The datasets generated and analysed during the current study are available from the corresponding author on reasonable request.Supplementary figures


We also investigated whether DCI, being an insulin-sensitizer would be able to counteract the expected stimulator activity of insulin on human granulosa cells (hGCs).d-chiroinositol (DCI) is a inositolphosphoglycan (IPG) involved in several cellular functions that control the glucose metabolism. DCI functions as second messenger in the insulin signaling pathway and it is considered an insulin sensitizer since deficiency in tissue availability of DCI were shown to cause insulin resistance (IR). Polycystic ovary syndrome (PCOS) is a pathological condition that is often accompanied with insulin resistance. DCI can positively affects several aspect of PCOS etiology decreasing the total and free testosterone, lowering blood pressure, improving the glucose metabolism and increasing the ovulation frequency. The purpose of this study was to evaluate the effects of DCI and insulin combined with gonadotrophins namely follicle-stimulating hormone (FSH) and luteinizing hormone (LH) on key steroidogenic enzymes genes regulation, t-test, as appropriate (P < 0.05) set for statistical significance.The study was conducted on primary cultures of hGCs. Gene expression was evaluated by RT-qPCR method. Statistical analysis was performed applying student CYP19A1, P450scc and insulin-like growth factor 1 receptor (IGF-1R) in dose–response manner. The presence of DCI impaired the increased expression of steroidogenic enzyme genes generated by the insulin treatment in gonadotrophin-stimulated hGCs.DCI is able to reduce the gene expression of CYP19A1, P450scc and IGF-1R. The ability of DCI to modulate in vitro ovarian activity of insulin could in part explain its beneficial effect when used as treatment for conditions associated to insulin resistance.Insulin acts as co-gonadotrophin increasing the expression of steroidogenic enzymes genes in gonadotrophin-stimulated granulosa cells. DCI is an insulin-sensitizer that counteracts this action by reducing the expression of the genes  Cucurbita ficifolia [The cis-1, 2, 4-trans-3, 5, 6-Cyclohexanehexol, also known as d-chiroinositol (DCI), is a six-carbon polyalcohol which belongs to the family collectively referred to as inositol which is a part of the B vitamin family. At cellular level inositols are incorporated into cell membranes as phosphatidyl-myo-inositol, the precursor of inositol triphosphate which acts as second messenger and regulates the activities of different hormones such as follicle-stimulating hormone (FSH) and insulin [DCI is considered as an insulin sensitizer since inositolphosphoglycan (IPG) mediators are involved in several cellular functions that control the glucose metabolism , 7.Moreover, impaired metabolism of IPG mediators as well as a deficiency in tissue availability of inositol were shown to cause insulin resistance , 9.Since DCI is synthetized by an epimerase that converts in vivo MI to DCI, several studies observed that a decreased DCI in urine as well as tissues of human subjects and animals with type 2 diabetes was accompanied by an increase in MI content , 11.Additional investigations demonstrated that the altered inositol excretion patterns in human and monkey urine were specifically related to the underlying insulin resistance (IR), rather than to the diabetes type. To explain the altered pattern of urine inositol excretion observed under IR, a defect in the epimerization process was hypothesized.When IR occurs, the conversion rate is affected, resulting in a decreased level of DCI in cells.In 2003 the European Society for Human Reproduction and Embryology (ESHRE) and the American Society for Reproductive Medicine (ASRM) established that patients can be affected by polycystic ovary syndrome (PCOS) when at least two conditions as anovulation or hyperandrogenism or increased ovarian volume are verified at the same time. However, PCOS patients are often affected by IR and it was hypothesized that a DCI deficiency, which functions as second messanger in the insulin signaling pathway , can be It has been demonstrated that DCI can positively affects several aspect of PCOS etiology , 14. In cytochrome P450 family 19 subfamily A member 1 (CYP19A1) aromatase and this effect has been shown to be so evident that insulin is considered by many as a co-gonadotrophin [Insulin has been reported to be able to interact with steroidogenic enzymes in granulosa and luteinic cells of the ovaries –20. Specotrophin –19, 21. otrophin –21.CYP19A1 and cytochrome P450 side-chain cleavage (P450scc). We also evaluated whether DCI, being an insulin-sensitizer would be able to counteract the expected stimulator activity of insulin on hGCs.The objective of this study was to expand on this argument, hence investigating the possible effect of insulin on the ovarian response to both the two gonadotrophins FSH and LH. We specifically investigated the modifications of the gene expression of two key genes in steroidogenesis, the aromatase n = 8) for this study were heathy, had regular menstrual cycles and had a mean age of 34 (±8). Patients underwent in vitro fertilization (IVF) because of male infertility. Clinical exclusion criteria adopted were: previous ovarian surgery, positivity for Chlamydia antibody testing (CAT), presence of ovarian cysts, history of pelvic inflammatory disease (PID), any known metabolic or endocrinological disease.Patients selected (Patients underwent IVF cycles according the gonadotrophin-releasing hormone (GnRH) antagonist protocol. Patients received recombinant human FSH  at a dose of at least 150 international units (IU) a day subcutaneously from day 2 or 3 of a spontaneous menstrual cycle. The GnRH antagonist, Ganirelix  or Cetrorelix , was next administered daily by subcutaneous injection (0.25 mg/d) from the day of the stimulation cycle when the first follicle reached 14 mm in size to the day of human chorionic gonadotrophin (hCG) administration. When follicles reached ≥18 mm, 10000 IU of hCG were administrated intramuscularly and 34–36 h later follicles were aspirated under patient sedation. hGCs were isolated from ovarian follicles of women undergoing oocyte retrieval for IVF protocol. Study approval was obtained from the local ethics committee and informed, written consent was obtained from each patient.3 cells/well) in McCoy 5A medium  supplemented with 5 % foetal bovine serum (FBS) South America , 2mM L-Glutamine, 1 % Penicillin/Streptomicin and 1 % Amphotericin B . Primary hGCs culture were mantained at 37 °C under a controlled atmosphere of 5 % CO2 for 6 days to avoid side effect due to IVF hormones treatment, and subjected to medium changes with fresh culture medium daily.hGCs were purified by centrifugation through a discontinuos Percoll  gradient as indicated in , and culhGCs primary cultures were initially incubated in starvation medium (McCoy 5A medium supplemented with 0.1 % FBS South America without antibiotics) for 12 h to synchronize cells before the treatments. hGCs were then incubated for 24 h with 0,1 IU/ml of long-acting insulin . hGCs insulin-treated where additionally incubated with 20 nM or 10 nM DCI  alone or in combination with either 5 μM rhFSH,  or 5 μM of recombinant human LH  for further 24 h. DCI and gonadotrophins were dissolved into starvation medium. Experiments were repeated in triplicate. Negative controls using corresponding amount of vehicle control for insulin treatment and for each of gonadotrophin used were performed. Comparison between negative controls performed and untreated cells showed no differences in terms of cells vitality, toxic effects or impaired gene expression caused directly by the vehicle in which substances were dissolved.n = 200) under inverted microscope PrimoVert . Percentage of viable cells were calculated and expressed as ratio between blue-stained dead cells and not colored viable cells.To assess the viability of gonadotrophin treated hGCs primary cultures, the Trypan Blue  exclusion test was performed. hGCs corresponding to each treatment and controls were submerged in 0.4 % Trypan Blue in 1X Dulbecco’s phosphate buffered saline  solution directly in the wells then immediately counted  gene. The specificity of each assay was validated by dissociation curve analysis and amplicons were separated by gel electrophoresis and imaged. Assay performance was validated by evaluating amplification efficiencies by means of calibration curves, and ensuring that the plot of log input amount versus DCq  has a slope. Each reaction was repeated in triplicate. Negative control reactions omitted templates.Collected hGCs after each treatment were immediately processed for total RNA extraction using commercial product Tri-Reagent®  following the manufacturer protocol. After an optional DNase I  digestion of 30 min at 37 °C the extracted RNA was evaluated and quantified by spectrophotometry using Nanodrop ND-1000  and 2 μg of RNA of each sample was reverse transcribed to cDNA using iScript™ cDNA Synthesis Kit  according to datasheet. 2 μL of cDNA of each sample was tested in triplicate in RT-qPCR using SsoAdvanced Universal SYBR® Green Supermix  following the conditions suggested by the manufacturer’s protocol. Primers used  set for statistical significance. The relative expression of each gene has been evaluated using the 2-ΔΔCt method [Statistical analysis was performed applying student t method  and was β3 integrin gene activation, expressed as ratio normalized by RpS7 reference gene on RT-qPCR assay, was studied as positive control . As Fig. RpS7 reference gene. Figure CYP19A1  gene expression while the co-incubation of DCI and 0,1 U of insulin in the culture system is not producing significatively differences between treated and untreated hGCs controls  revealed that DCI is able to directly reduce ols Fig. .Fig. 5DoCYP19A1 and P450scc. Moreover, DCI may modulate the stimulatory effects on steroidogenic genes mediated by both gonadotrophins and insulin.In the present study we demonstrated that insulin and DCI are able to affect directly the gene expression of two pivotal steroidogenic enzymes gene namely β3 integrin gene. Integrins are membrane receptors involved in cells-extracellular matrices adhesion and in the signal transduction that are differentially and stage-specifically expressed on hGCs [β3 integrin gene expression in all the hGCs primary cultures employed in this study.The efficiency of the cultural system in which DCI treatments affected the genes regulation in hGCs primary cultures was evaluated trough the analysis of the expression of  on hGCs . It was  on hGCs  as well  on hGCs , 27. For on hGCs –30. More on hGCs . Based oCYP19A1 and P450scc genes in dose–response manner. P450scc enzymes catalyze many reactions involved in synthesis of cholesterol and steroids and togheter with the aromatase CYP19A1 are required to regulate estradiol and progesterone production within the ovary [In addition, our analyses show that DCI acts directly on steroidogenic enzymes gene regulation of hGCs reducing mRNA expression of both he ovary .CYP19A1 and P450scc genes [CYP19A1 and P450scc gene expression according with previously published data [CYP19A1 and P450scc were significatively induced if compared to the untreated hGCs control.However, because the mature granulosa-lutein cells used for this in vitro study may not reflect the in vivo condition, the experiments were also conducted in presence of gonadotrophins and insulin. Both the gonadotrophins  induce expression of cc genes , 34 althcc genes , 36. It cc genes , 38 and cc genes , 40. In 2+-dependent protein phosphatases (MPPs) family which control the glucose metabolism [Since it was also reported that DCI plays a role as second messengers in the classical phosphorylation signaling pathways activated by insulin triggering the activation of Mgtabolism , we inveNotoriously, insulin exerts its function not only by binding insulin receptors present on the surface of target cells but also functioning as ligand for IGF-1R . The typIn the last years one of the most studied of the in vivo pathology related to infertility was the PCOS. The PCOS is characterized by elevated levels of insulin and IGF-1R  and it hIGF-1R expression in a dose-dependency manner.In the present study, we showed not only that DCI is able to balance the additional stimulatory effect on steroidogenic enzyme gene of gonadotrophins stimulated hGCs, but also we firstly demonstrated that incubation of hGCs with increasing dosage of DCI resulted in a decreased CYP19A1, P450scc and IGF-1 receptor. The ability of DCI to modulate in vitro ovarian activity of insulin could at least in part explain its beneficial effect when used as treatment for conditions associated to insulin-resistance.In conclusion, in the present study we could confirm the effect of insulin as co-gonadotrophin on granulosa cells from the ovaries and we could demonstrate that DCI, an insulin-sensitizers counteract this action. This was evident when the expression of several genes was investigated, such as aromatase


Restricted lobar cerebral microbleeds (CMBs) and cortical superficial siderosis (CSS) are the characteristic markers of cerebral amyloid angiopathy (CAA). However, their effects on clinical features has not been evaluated well. The purpose of this study is to investigate the clinical implication of these markers in clinical-radiologically diagnosed CAA. A total of 372 patients with possible or probable CAA who met the modified Boston criteria were recruited in a memory clinic setting. Cortical thickness was measured using surface based methods. Presence of restricted multiple lobar CMBs were independently associated with cortical thinning across the entire cortical regions while presence of CSS was independently associated with cortical thinning primarily in the bilateral frontal region. Presence of restricted multiple lobar CMBs was associated with impairment in all cognitive domains such as attention, language, visuospatial, memory and frontal executive functions while presence of CSS was associated with attention and frontal dysfunction. The relationships of restricted multiple lobar CMBs or CSS with cognitive impairment were partially mediated by thinning in the corresponding cortical regions. Our findings suggested that restricted multiple lobar CMBs and CSS affect distinctive clinical features, providing new insights into potential mechanisms in CAA. Cortical superficial siderosis (CSS), which is linear deposits of the blood-breakdown residues within the subarachnoid space, the leptomeninges and the superficial layers of cerebral hemisphere. Strictly lobar CMBs and CSS have been suggested as characteristic neuroimaging markers of cerebral amyloid angiopathy (CAA) and have been recently adopted as clinical diagnostic markers even without intracranial haemorrhage (ICH)3. In fact, 90% of symptomatic CAA patients diagnosed by the presence of multiple lobar CMBs without ICH harboured moderate to severe CAA on neuropathology4. In addition, CSS was commonly (60%) observed in pathologically confirmed CAA patients3.Cerebral microbleeds (CMBs) are defined as small, round dark-signal lesions on T2* gradient-echo (GRE) magnetic resonance imaging (MRI)5, and CAA pathology seems to be associated with cognitive impairment independently of Alzheimer’s disease (AD) or other neurodegenerative pathologies8. A recent study also suggested that CAA might show cortical atrophy9, which has an important role in cognitive impairment. Given that lobar CMBs and CSS may arise from distinct vasculopathic mechanisms 10, lobar CMBs and CSS may affect distinctively clinical features. Furthermore, it would be reasonable to expect that multiple lobar CMBs and CSS might be associated with cortical thinning, which in turn leads to cognitive impairment because cortical atrophy may be final common pathway of amyloid beta (Aβ) and cerebrovascular disease for cognitive impairments11.Previous studies showed that 60% of pathologically diagnosed CAA patients have cognitive impairmentIn this study, we investigated the relationship between CAA haemorrhagic markers and cognition in a unique cohort of clinical-radiological CAA patients. We hypothesized that CAA haemorrhagic markers distinctively affected clinical features including cortical thickness and cognitive impairments. We also hypothesized that cortical thinning mediated the relationships between CAA haemorrhagic markers and cognition.3. Their demographic and clinical characteristics are summarized in Supplementary Table APOE ε4, poorer cognitive status, and more severe WMH among non-CAA, possible CAA, and probable CAA groups respectively  patients met the possible  or probable  CAA criteriaAPOE ε4 allele than CAA without multiple lobar CMBs (P < 0.003). There were no differences in demographics and vascular risk factors between CAA with CSS (n = 73) and CAA without CSS (n = 299) (Table There were no differences in demographics and vascular risk factors between CAA with multiple lobar CMBs n = 150) and those without multiple lobar CMBs (n = 222) /164 (5.1%) of elderly people over 55 years of age fulfilled the Boston criteria for possible/probable CAA in our cohort. Lobar CMBs were observed in 10.6% and 44.0% of them had multiple lobar CMBs. Also, 2.7% of patients showed CSS. Our findings were generally consistent with previous studies showing that 13.7% of general population had lobar CMBsAPOE ε4, poorer cognitive status, and more severe deep and periventricular WMH were the most prominent in probable CAA by possible CAA and non-CAA, which are consistent with previous studies. Furthermore, their differences between possible CAA and non-CAA groups occurred. Considering almost of all our possible CAA patients have only a single lobar CMB, our findings might potentiate the concept that a single lobar CMBs at least observed in memory clinic patients may represent an early sign of a widespread vasculopathy rather than just misidentification of normal vessel structures4.We found that older age, a higher frequency of 15. A recent study from our group showed that changes in lobar, but not deep, CMBs were associated with cognitive decline over three years16. Studies based on CAA patients, however, consistently reported that CAA patients showed cognitive impairment8. Given that multiple lobar CMBs reflect a severe underlying CAA, multiple lobar CMBs might be associated with decreased cognition. In fact, several studies suggested that lobar CMBs were associated with frontal executive function17, or impairment in multiple cognitive domains18. Although CSS is known to be related to impaired cognition19, the specific pattern of cognitive impaired has not been investigated to date.Our first major finding was that the association between multiple lobar CMBs or CSS and cognitive impairment was distinct in terms of the specific cognitive domains affected. Multiple lobar CMBs were associated with cognitive impairment in multiple domains while CSS was correlated primarily with frontal dysfunction. Previous studies have shown inconsistent results of the clinical influence of CMBs6. A previous study also showed that lobar CMBs affected gray matter atrophy and hypometabolism in the temporal lobe20. In contrast to the present study, a recent study revealed that decreased cortical thickness in CAA patients did not correlate with lobar CMB, but related to impaired vascular reactivity9. This discrepancy most likely reflects differences in study population . However, in the present study, associations between haemorrhagic markers and cortical thinning remained significant after controlling for WMH that might be possible confounder. Our findings, therefore, suggested that these CAA haemorrhagic markers are considered not only a radiologic indicator of the presence of underlying CAA but also determinant of the clinical phenotypes of CAA.We also found that multiple lobar CMBs were associated with thinning in entire cortical regions, while CSS were associated with thinning in the frontal and temporal regions. To our knowledge, the relationship between focal haemorrhagic imaging markers and more diffuse brain structural changes has not been established yet. A recent study revealed that CAA patients had structural network disruption and neurological dysfunction4, they are likely to be associated with more parenchymal Aβ or cortical micro-infarcts. Parenchymal Aβ burden or micro-infarcts are also reported to be associated with cortical thinning as well as cognitive impairment22. Furthermore, previous studies from our group have shown that parenchymal Aβ burden affected cognitive impairment with and without the mediation of cortical thinning11. Therefore, our findings suggested cortical thinning might play an important role in the development of cognitive impairments in patients with CAA.Our second major finding was that cortical thinning partially mediated the associations between key haemorrhagic imaging markers of CAA and cognitive impairment in the corresponding domains. The exact mechanisms by which these CAA haemorrhagic markers lead to cognitive impairment remain to be elucidated. However, given that haemorrhagic imaging marker burden might reflect more severe underlying CAA pathologyThe strengths of our study are its standardized MRI imaging and neuropsychological protocols in a large sized CAA cohort in a memory clinic. However, some limitations need to be acknowledged. The main limitations of our study include the lack of pathological data of our clinical-radiologically diagnosed CAA patients. We also note that the sensitivity and specificity of a possible CAA diagnosis, based on the presence of a single lobar CMBs might be low. Considering that CAA with haemorrhagic markers reflect moderate to severe form of CAA, our data should be interpreted with caution. Finally, we did not measure micro-infarcts and determine whether micro-infarcts affect our findings.Despite these limitations, our findings suggest that CAA might be classified into several phenotypes based on advanced neuroimaging and according to the presence and burden of key haemorrhagic markers of the disease. Our findings are hypothesis-generating and after further validation in other cohorts and clinical settings, will advance our understanding of potential CAA subtypes with relevance for designing and interpreting future treatment trials.25. Our recruitment was based on memory clinic enriching for patients with clinical Alzheimer’s disease, subcortical vascular dementia, MCI, or SMI and only a small minority had frontotemporal lobar dementia, dementia with Lewy body, or other degenerative dementia. This study employed a standardized diagnostic assessment protocol including structural magnetic MRI for neurodegeneration and cerebrovascular disease and detailed neuropsychological tests.A total of 3,216 participants were enrolled in the Samsung Medical Center Neuroimaging Study Registry from July 2007 to December 2013. Clinical diagnosis was established at a multi-disciplinary conference applying standard research criteria for SMI, MCI and dementia syndromes3.Using this registry, we identified 372 patients with possible or probable CAA who met the modified Boston criteria, based on the presence of CSS and/or lobar CMBs12/folate, syphilis serology, and/or thyroid function issues), or the presence of structural lesions  on conventional brain MRI scans, or with psychiatric illnesses such as schizophrenia.We excluded patients with the presence of secondary causes of cognitive deficits  T1 images at Samsung Medical Center using the same kind of 3.0 T MRI scanner . The following parameters were used for the T2* GRE images: axial slice thickness, 5.0 mm; inter-slice thickness, 2 mm; repetition time (TR), 669 ms; echo time (TE) 16 ms; flip angle, 18°; matrix size, 560 × 560 pixels. We acquired 3D T1 images with the following imaging parameters: sagittal slice thickness, 1.0 mm, over contiguous slices with 50% overlap; TR of 9.9 ms; TE of 4.6 ms; flip angle of 8°; and matrix size of 240 × 240 pixels, reconstructed to 480 × 480 over a field of view of 240 mm.1: (1) homogeneous signal losses with blooming effects on T2* images, (2) round or ovoid lesions with a 10 mm diameter cut-off, (3) lesions at least half surrounded by brain parenchyma, and (4) distinct from other potential mimics such as iron or calcium deposits, or vessel flow voids.Lobar CMBs were defined as microbleeds located in lobar areas and meeting the following consensus criteria26 with recommendation criteria as follows27: (1) bilinear track-like hypointensities on T2* images surrounding or within a cerebral sulcus; (2) absence of corresponding hyperintense signals on FLAIR images; (3) supratentorial location; and (4) exclusion of a previous ICH associated CSS .CSS was defined as chronic blood residual products in superficial layers of the cerebral cortex or subarachnoid areaFour experienced neurologists, who were blinded to clinical information rated lobar CMBs and CSS on T2* images. Intra-class correlation coefficient ranged from 0.87 to 0.91 for lobar CMBs and from 0.82 to 0.96 for CSS.28.To estimate the severity of white matter hyperintensities (WMH) in deep and periventricular white matter, we used the Fazekas rating scale29. The N3 algorithm was used to correct the images for intensity-based non-uniformities30 caused by the non-homogeneities in the magnetic field. Then, the registered and corrected images were classified into white matter, gray matter, cerebrospinal fluid, and background, using a 3D stereotaxic brain mask and the Intensity-Normalized Stereotaxic Environment for Classification of Tissues algorithm. The surfaces of the inner and outer cortex were automatically extracted using the Constrained Laplacian-Based Automated Segmentation with Proximities algorithm31.T1-weighted images were processed using the standard Montreal Neurological Institute anatomical pipeline. With a linear transformation, native MRI images were registered into a standardized stereotaxic space32. Cortical thickness was defined as the Euclidean distance between the linked vertices of the inner and outer surfaces31. The thickness value was spatially normalized using surface-based two-dimensional registration with a sphere-to-sphere warping algorithm. Thus, the vertices of each subject were nonlinearly registered to a standard surface template34. Cortical thickness was subsequently smoothed using a surface-based diffusion kernel in order to increase the signal-to-noise ratio. We chose 20 mm full-width at half-maximum as the kernel size to maximize statistical power while minimizing false positives35. For global and lobar regional analysis, the data of 30 normal subjects that had previously been manually categorized to lobes with high inter-rater reliability36 were registered to the template. The template then took the label of maximum probability in each vertex.Cortical thickness values were calculated in the native space rather than Talairach space because of the limitations in linear stereotaxic normalization. As we transformed MR volumes in native space into stereotaxic space with a linear transformation matrix, the inverse transformation matrix was applied to the cortical thickness models to reconstruct them in native space37. Individual cortical surface of each subject was registered to the precategorized template and divided into frontal, temporal, parietal, and occipital lobes via automated processes. Averaged values of the thickness of the whole vertex in each hemisphere and lobar region were used for global analysis.The presence of extensive WMH in the MRI scans made it difficult to completely delineate the inner cortical surface with the correct topology due to tissue classification errors. To overcome this technical limitation, we automatically defined the WMH region using a FLAIR image and substituted it for the intensity of peripheral, normal-appearing tissue on the high-resolution T1 image after affine co-registration, as described in earlier studies39. We derived domain composite scores using the summation of selective tests scores for each subdomain. The raw scores of digit span forward and backward made up the score of attention domain . The language domain score was derived from the raw score of the Boston Naming Test . The RCFT copy score were used for visuospatial function domain . The memory domain was calculated from the sum of immediate-recall score, delayed-recall score, and a recognition score from the Seoul Verbal Leaning and RCFT . Frontal executive function domain was conducted using phonemic and semantic controlled oral word association test .All patients underwent neuropsychological tests using the Seoul Neuropsychological Screening Battery (SNSB)2 for categorical variables and the analysis of variance for continuous variables were performed to compare the probable CAA, possible CAA, and non-CAA groups. Trend analyses of age, APOE genotype, cognition level and WMH severity were performed to evaluate tendency among the non-CAA, possible CAA and probable CAA groups. Both lobar CMBs and CSS were categorized according to a median number as dummy variables to classify this cohort into the severe and mild CAA groups; no or single lobar CMBs group versus multiple lobar CMBs group and CSS absent group versus CSS present group. To assess the effects of multiple lobar CMBs or CSS presence on cortical thickness, linear regression analyses were performed after controlling for age, sex, education, ICV, WMH and multiple lobar CMBs or CSS presence. To identify the effects of multiple lobar CMBs or CSS presence on cognition, we also used linear regression analyses after controlling for age, sex, education, WMH and lobar CMBs or CSS.Chi-squared tests for categorical variables and t tests for continuous variables were performed to compare the CAA and non-CAA groups. Fisher exact test and global xP) from the regression analyses. Regional cortical thickness was compared using Matlab 7.11 for Windows .To investigate the topography of cortical thinning associated with multiple lobar CMBs or CSS presence, we entered these two markers simultaneously in a general linear model as predictors for regional cortical thickness on a vertex-by-vertex basis. Covariates included age, gender, education, ICV, WMH and another CAA haemorrhagic marker for each lobar CMBs or CSS. The resulting statistical maps were thresholded, using the false discovery rate theory at a Q value of 0.05, after pooling the probability values . Statistical significance was defined as two-tailed Table 1


Here we report that LPS triggers a monocyte phenotype permissiveness for lytic infection directly correlating with LPS concentration. In contrast, addition of LPS directly to latently infected monocytes was not sufficient to trigger viral reactivation which is likely linked with the failure of the monocytes to differentiate to a DC phenotype. Interestingly, we observe that this effect on lytic infection of monocytes is transient, appears to be dependent on COX-2 activation and does not result in a full productive infection. Thus LPS stimulated monocytes are partially permissive lytic gene expression but did not have long term impact on monocyte identity regarding their differentiation and susceptibility for the full lytic cycle of HCMV.Human cytomegalovirus (HCMV) infection of myeloid cells is closely linked with the differentiation status of the cell. Haematopoietic progenitors and CD14+ monocytes are usually non-permissive for lytic gene expression which can lead to the establishment of latent infections. In contrast, differentiation to macrophage or dendritic cell (DC) phenotypes promotes viral reactivation or renders them permissive for lytic infection. The observation that high doses of Lipopolysaccharide (LPS) drove rapid monocyte differentiation in mice led us to investigate the response of human monocytes to HCMV following LPS stimulation  Although these cells give arise to multiple white blood cell populations the carriage of viral genomes is restricted to the myelo-monocytic lineage in healthy individuals8. Importantly, the differentiation of monocyte and dendritic cell (DC) precursors to a mature macrophage or DC phenotype is sufficient to induce lytic viral gene expression and, ultimately, result in the reactivation of infectious virus production12. This differentiation-dependent control of HCMV latency and reactivation is also reflected in the permissiveness of these same cell types for lytic infection17 and thus understanding the contribution of cellular differentiation to HCMV infection in the myeloid lineage contributes to our understanding of the factors that control viral infection.Primary infection with human cytomegalovirus is usually asymptomatic in the healthy host and results in the establishment of a lifelong latent infection. One major site of latency is the haematopoietic progenitor cell population resident in the bone marrow19. A body of literature now reports the identification and characterisation of a number of sub-populations of DCs which can be differentiated from each other by cell surface markers, anatomical localisation and cytokine production as well as mechanistic differences which has largely been based on murine studies20. The paucity of circulating DCs in the peripheral blood compartment has led researchers to use in vitro differentiation of CD34+ or CD14+ precursors to study the function of these cells22. These studies include HCMV where a number of laboratories have employed the in vitro differentiation of progenitor cells to document the pivotal role cellular differentiation plays in latency and reactivation as well as lytic infection28.First identified by Steinman and colleagues in the 1970s, DCs are a minor population of professional antigen presenting cells (APCs) that are able to activate primary adaptive T cell immune responsein vitro. Importantly, a number of these experimental observations have been re-capitulated ex vivo through analyses of naturally latent cell types. Specifically, CD34+ cells and monocytes are not sites of viral reactivation7. In contrast, DCs isolated directly ex vivo from healthy seropositives display evidence of lytic IE transcription and, when co-cultured with HFFs, can support HCMV reactivation12. Thus the models utilising in vitro differentiation of myeloid precursors to DCs can be exploited to study HCMV reactivation. However, a caveat is that whilst in vitro systems are informative they rely on relatively long term culture of DC populations that are then, to some degree, mapped onto the ontogeny of DCs in vivo.Studies of HCMV rely largely on the long term culture of experimentally infected CD34+ or CD14+ cells to study viral reactivation 29. The underlying premise was to show that systemic delivery of high doses of the endotoxin lipopolysaccharide LPS generated a large expanded population of DCs within 2–3 days in these animals. This putative DC population was hypothesised to be derived from circulating monocytes consistent with monocytes retaining the capacity to differentiate into DCs in vivo. Given our own interest in the role of DCs in reactivation we thus asked whether human monocytes treated in vitro under the same conditions could trigger viral reactivation - potentially providing a rapid model for studying HCMV reactivation.However, a provocative study in the murine model pointed towards the rapid activation of circulating monocytes to a DC phenotype following an endotoxin insultHere we report that treatment of monocytes with high concentrations of LPS prior to infection generated a cell type permissive for lytic immediate-early (IE) gene expression. The infection rate was LPS dose-dependent with higher doses resulting in increased numbers of cells being IE positive. However, unlike in DCs, the infection was abortive with little evidence of DNA replication or virus production evident in these cells. Furthermore, the LPS induced permissiveness for lytic infection was transient and was sensitive to COX-2 inhibition. In contrast, the stimulation of long term latently infected monocytes with LPS failed to trigger IE gene expression from latency. The basis for these differences could not be attributed to a global defect in the ability of latently infected monocyte populations to respond to LPS. These data support a hypothesis that multiple mechanisms unique to the regulation of latent (but not lytic) IE gene expression need to be overcome for reactivation to ensue in differentiated cell types.CD14+ monocytes were isolated from healthy seronegative donors and stimulated with increasing concentrations of LPS. Three days post LPS stimulation, cells were infected with the Merlin strain of HCMV and analysed for IE protein expression by immuno-fluorescent microscopy 24 hours post infection. At the highest dose of LPS clear evidence of IE protein expression was observed in the monocytes Fig. . Log dilHaving addressed the effect of dose we next addressed the impact of time on permissiveness. Thus cells were incubated with 500 ng/ml LPS and infected at 1–3 days post stimulation Fig. . Again wThroughout these initial studies it was evident that a minor proportion of cells were loosely adherent and displayed fewer morphological changes associated with monocyte activation/differentiation (i.e. less granular and fewer dendritic-like processes). Thus we performed a second analysis where both the adherent and non-adherent fractions were analysed independently. Following infection, the loosely adherent cells were washed off and cytospun onto glass slides and stained for viral infection Fig. . As obseTo address whether the observed expression of IE proteins was abortive or resulted in the production of infectious virus monocytes stimulated with LPS for 3 days were infected with HCMV and then analysed with a gB qPCR to measure viral DNA replication. HCMV DNA replicated in HFFs resulting in a 2.5 log increase in viral copy number from 24 to 96 hpi with replication being sensitive to ganciclovir Fig. . In contA major research interest is to foster an understanding of the mechanisms that govern the induction of robust lytic IE gene expression from latently infected cells as the first stage required for HCMV reactivation. Thus we next tested whether induction of IE gene expression from latency was evident under culture conditions that drive monocyte permissiveness for lytic IE gene expression upon infection. Monocytes were infected with HCMV and were defined as latently infected by the concomitant detection of UL138 gene expression and minimal levels of major IE gene expression Fig. . These c31.The data thus far suggested that whilst LPS stimulation of monocytes rendered them permissive for lytic IE gene expression it was not sufficient for the induction of IE gene expression from latency. One possible explanation for these differences was that LPS induced effects on uninfected monocytes could occur through secondary messengers that are antagonised in latently infected cell cultures through modulation of the secretome34 and long term monocyte cultures35 and, furthermore, IL-6 has been shown to play a role in the reprogramming of differentiation in monocytes36. Thus we asked whether differential IL-6 activity could explain the different outcomes observed during reactivation and primary infection. The first experiments addressed whether the lack of detectable reactivation in the LPS monocytes was simply linked with a decrease in IL-6 production in response to LPS stimulation and thus a reduction in paracrine signalling in the cultures. As expected, uninfected monocytes stimulated with LPS produced a burst of IL-6 - the levels of which decreased over time  after multiple washes. At the 72 hour time point, the cells were then infected with HCMV and immuno-stained for IE gene expression Fig. . UnstimuA possible explanation for these transient effects was the hyper-activation of intracellular pathways that contribute to lytic infection during the initial stages of viral infection but are not capable of reversing viral latency. To investigate this further we tested the ability of a panel of inhibitors to block the LPS mediated effect on monocytes we had observed. Using inhibitors of downstream signalling pathways reported to be LPS responsive in various cell culture models we detected that the LPS induced phenotype was most potently inhibited by the COX-2 inhibitor, indomethacin Fig. . This CO24. In this study, we sought to address whether high doses of LPS could render normally non-permissive monocytes permissive for HCMV infection and reactivation. The rationale for this approach was driven by a previous study in the murine system which showed that circulating monocytes rapidly populated the DC pool in response to high concentrations of LPS29 – potentially representing a new, quicker approach to study HCMV reactivation in vitro.Permissiveness for lytic infection or for the reactivation of HCMV from latency in the myeloid lineage is intimately associated with the differentiation status of the cellin vitro. A caveat of initial analyses was the identification of a sub-population of ‘monocytes’ that appeared resistant to HCMV infection even if treated with LPS  signalling is impaired in undifferentiated latently infected cells.32. What this suggests is that the mechanisms governing the maintenance of long term latency are not wholly equivalent to the mechanisms important during the initial stages of infection in non-permissive cells. The mechanisms dictating long term latency are likely a concert of viral and cellular factors that promote the long term repression of lytic gene expression via the utilisation of histone modifying enzymes, chromatin structure, miRNA function and re-partitioning of cell signalling pathways43. In contrast, during those initial stages the intrinsic hostile cellular environment the virus encounters – and likely a failure to overcome that - is the major determinant45. Consequently, studying the basis of why the addition of LPS to latently infected monocytes does not drive viral reactivation can contribute to defining the mechanisms that do.Central to our own research interests was the observation that the treatment of monocytes with LPS failed to trigger IE gene expression in latently infected cells. This clearly suggested that an intrinsic block to reactivation was not relieved under these differentiation/activation conditions in contrast to when the cells are incubated with IL-4/GM-CSF to make classical DCs48. LPS is recognised by the pattern recognition receptor TLR4 which then signals downstream through multiple pathways49. HCMV has also been shown to bind and engage with TLRs – notably TLR250 – but also TLR4 in monocytic cells51. Potentially, infecting monocytes at high MOIs may substitute for the LPS effects here and render monocytes transiently permissive for IE gene expression through delivery of high numbers of viral particles activating TLR4. It is possible that such a scenario could occur during viraemia and thus could represent a host response that is advantageous. The abortive expression of IE proteins in an absence of the expression of key immune evasion genes could facilitate a more effective T cell immune response and promote elimination of infected cells. It is this principle of inducing abortive IE protein expression that underpins the strategy of the use of HDAC inhibitors to clear latently infected cells52.Why high doses of LPS makes monocytes permissive for IE gene expression is also an interesting question. It potentially could also explain studies which have suggested that monocytes and myeloid cells display a level of permissiveness for HCMV infection under certain conditions56. Most recently, they report that the HCMV genome can take upwards of 3 days to enter the nucleus55. Clearly, in these studies we are observing IE protein expression by 24 hours post infection and thus it is possible LPS is activating the cells to respond differently to infection circumventing this delayed pathway. Indeed, our observation that the LPS effect is COX-2 dependent in the monocytes may be linked to this. It has been previously described that COX-2 plays an important role in the replication and pathogenesis of CMV during lytic infection59. However, the major impact in fully permissive fibroblasts is on the switch from IE72 to IE86 protein expression and, ultimately, the production of new virions58. Thus during lytic replication COX-2 activation plays a key role during the later stages of viral infection and, importantly, post- IE and therefore cannot be directly related to the LPS effects we are reporting. However, a less well explored role of COX-2 is the potential of this pathway to impact on endocytosis and virus infection60. HCMV has evolved to utilise multiple entry pathways61 and thus the priming events we see with LPS may reflect a change in the pathway utilisation of HCMV due to hyper-activation of a COX-2 sensitive endocytic pathway in the monocytes. Although highly speculative, entry via this route may circumvent the usual entry pathway allowing the  initiation of viral gene expression. However, a post-IE block remains active in normally non-permissive cells and thus the virus does not continue into a full productive infection. An alternative, but linked, explanation may involve the delivery of tegument. A contributing factor to latent infection has been hypothesised to be the failure to deliver the major virion transactivator, pp71, to the nucleus in non-permissive myeloid cells62. Thus an equally plausible explanation could be that pp71 does traffic to the nucleus if the cells are primed with LPS.Alternatively, the addition of LPS could be impacting on the normal entry pathways active in the monocyte. Studies, mainly from the Yurochko laboratory, implicate the presence of a unique entry pathway into monocytesin vitro do not appear to support the generation of a DC phenotype which is supported by both phenotypic evidence and, indirectly, the failure of HCMV to replicate in these cells. Therefore it is likely that LPS acts in concert with other cytokines in vivo to drive the DC phenotype observed in the murine model.Here we report the transient induction of a cellular environment in monocytes by LPS that supports IE lytic gene expression upon infection. In contrast, the effects of LPS on latent HCMV in monocytes is minimal suggesting that LPS fails to overcome additional blocks controlling IE gene expression during latency in monocytes. Understanding the molecular basis for these differences could enhance our understanding of the mechanisms governing HCMV reactivation. Importantly, we report that high doses of LPS All studies on monocytes were performed with local approval from either the Cambridge or UCL Local Research Ethics Committee and all experiments were performed under the guidelines and regulations set out by the committees. Informed consent was given locally unless excess material from NHS Blood Transfusion Service  was used where donors provide consent at point of donation for material to be used anonymously in research studies.2. CD14+ mononuclear cells were directly isolated from HCMV-seronegative blood and immature DCs were generated as described previously. Briefly, peripheral blood mononuclear cells (PBMCs) were prepared by centrifugation on a Ficoll-Hypaque  density gradient. Magnetic-activated cell sorting using CD14+ antibody-conjugated MicroBeads  allowed collection of a CD14+ mononuclear cell-enriched population, which were maintained in X-VIVO 15 serum free media . To promote differentiation to a MoDC phenotype, cultures were stimulated with IL-4 (100 ng/ml) and GM-CSF (100 ng/ml) for 6 days . Loosely adherent cells were collected by moderate aspiration and transferred to fresh wells. Mature DCs were generated by adding LPS in fresh media .Human foreskin fibroblasts (HFFs) were maintained in Dulbecco’s minimal essential medium containing 10% fetal calf serum (DMEM-10)  and incubated at 37 °C and in 5% CO32. The soluble IL6 receptor  was used at an equivalent concentration to IL-6.Alternatively, monocytes were incubated directly with LPS (50–5000 ng/ml) for 1–3 days with no prior differentiation as described in the results. For experiments analyzing IL-6 activity, IL-6  and neutralizing IL6 antibody  were used at concentrations previously shown to have activity in HCMV reactivationTo measure IL-6 in the culture medium an IL-6 ELISA quantikine kit was used as described by manufacturer .The following inhibitors all Calbiochem  unless stated were used at concentrations known to inhibit activity of their target. ERK , JNK , p38  and COX-2  were added to media 1 hour prior to stimulation with LPS and/or subsequent infection with HCMV. Ganciclovir  was used at 10 ug/ml to inhibit viral DNA replication.63.To culture TB40/e and Merlin strains of HCMV they were first cultured in ARPE-19 cells and then amplified following a single round of replication in HFFs. Virus was isolated and purified on sorbitol gradients as described previouslyFor DNA replication analysis experiments, infected monocytes were washed in PBS and then incubated for 1 hour with 2 mg/ml Proteinase K solution and the media replaced with fresh media to remove un-internalised virus from the cell surface.To study latency CD14+ monocytes were cultured for at least 4 hours in X-vivo 15 following isolation and then infected with a preparation of the clinical isolate Merlin . After 3 hours, infected cells are washed and cultured in fresh X-vivo 15 media for 7 days. After 3 days, media is exchanged again and fresh media containing cytokines that promote DC differentiation are added as described before. Virus production from reactivating mature MoDCs or from LPS stimulated monocytes was assayed by IE qRT-PCR 24 hours post stimulation or after following co-culture on a confluent monolayer of HFF with samples of supernatant taken at regular intervals and used to inoculate fresh HFF to test for infectious virus by indirect immuno-fluorescent staining.Infected cells were rinsed in PBS and fixed for 10 minutes in 4% paraformaldehyde at room temperature. After permeabilizing with 0.1% Triton-X-100 in PBS, cells were incubated with monoclonal mouse anti-IE antibody (Millipore) (1:1000 dilution in PBS) for 1 hour at room temperature. After washing with PBS, the bound antibodies were detected using Alexafluor 594 nm -conjugated goat anti-mouse immunoglobulins (1:1000 dilution in PBS) together with nuclear stain DAPI (300 nM in PBS) in the dark for 1 hour at room temperature. After washing with PBS, infected cells were visualised using a Nikon immunofluorescence microscope and were quantified using ImagePro WCIF ImageJ software . Percentage infection was calculated by dividing the number of infected cells (red) by the total number of cells (blue) from at least 4 fields of view.6 cells using the RNAeasy kit as described by the manufacturer  Residual genomic DNA was removed by a DNAse I digestion  followed by production of first-strand cDNA using the Promega RT system. For quantitative PCR, primers that amplified the IE region of HCMV were used64. The following reaction conditions were used in a 96 well plate format with forward primer AGC GCC GCA TTG AGG A, reverse primer CAG ACT CTC AGA GGA TCG GCC and probe ATC TGC ATG AAG GTC TTT GCC CAG TAC ATT (Fam probe with TAMRA quencher). PCR reactions were performed using Taqman MasterMix  in a 7500HT machine . Actin was amplified using a VIC-actin commercial probe  and statistical analysis and interpretation performed as described65.Total RNA was extracted from 106 cells were resuspended in 600 ul of buffer A , lysed with 10% SDS (125 ul) and then incubated with 5 M sodium percholorate (150 ul). DNA was isolated by phenol:chloroform extraction and isopropanol precipitation. DNA copy number was then quantified using gB qPCR used in diagnostic assays66.To assay DNA replication, total DNA was isolated using a sodium perchlorate method described previously which has been optimized for the isolation and detection of viral genomes from naturally latent mononuclear cells (23). Briefly, 106 cells/ml were suspended in X-vivo 15 media in capped polypropylene FACS tubes (BD) pulsed with LPS, IL-4/GM-CSF to generate DCs or, 20 ng/ml M-CSF  for 1, 3 or 6 days incubated at 37 °C 5% CO2. Cells were pelleted at 400 g for 5 minutes and 105 cells per staining condition were stained with monoclonal antibodies specific for CD14-APC, CD83-APC, CD86-PE, CCR5-APC, MHC Class II (HLA-DR)-APC from BD Pharmingen , CD11b-FITC, CD209 (DC-SIGN)-PE, MHC Class I-PE from BioLegend  and CD80-APC from Abcam . Isotype controls IgG1-FITC, IgG1-APC, IgG2a-PE, IgG2a-APC in the dark at room temperature for 30 mins.Monocyte at 10Following washing in PBS, the cells were pelleted at 400 g for 5 minutes and were re-suspended in 500 μl of phosphate buffered saline (PBS) before analyzing by flow cytometry (BD AccuriC6). Data handling was performed using AccuriC6 and FLOWJO software.Tests for statistical significance were performed using the non-parametric Mann Whitney U test on paired samples. Statistical significance was designated for any p value lower than 0.05.