Assessing the gain of biological data integration in gene networks inference

Background: A current challenge in gene annotation is to define the gene function in the context of the network of relationships instead of using single genes. The inference of gene networks (GNs) has emerged as an approach to better understand the biology of the system and to study how several components of this network interact with each other and keep their functions stable. However, in general there is no sufficient data to accurately recover the GNs from their expression levels leading to the curse of dimensionality, in which the number of variables is higher than samples. One way to mitigate this problem is to integrate biological data instead of using only the expression profiles in the inference process. Nowadays, the use of several biological information in inference methods had a significant increase in order to better recover the connections between genes and reduce the false positives. What makes this strategy so interesting is the possibility of confirming the known connections through the included biological data, and the possibility of discovering new relationships between genes when observed the expression data. Although several works in data integration have increased the performance of the network inference methods, the real contribution of adding each type of biological information in the obtained improvement is not clear. Methods: We propose a methodology to include biological information into an inference algorithm in order to assess its prediction gain by using biological information and expression profile together. We also evaluated and compared the gain of adding four types of biological information: (a) protein-protein interaction, (b) Rosetta stone fusion proteins, (c) KEGG and (d) KEGG+GO. Results and conclusions: This work presents a first comparison of the gain in the use of prior biological information in the inference of GNs by considering the eukaryote (P. falciparum) organism. Our results indicates that information based on direct interaction can produce a higher improvement in the gain than data about a less specific relationship as GO or KEGG. Also, as expected, the results show that the use of biological information is a very important approach for the improvement of the inference. We also compared the gain in the inference of the global network and only the hubs. The results indicates that the use of biological information can improve the identification of the most connected proteins.

The SUCEST-FUN regulatory network database: Designing an energy grass

Modern sugarcane cultivars are complex hybrids resulting from crosses among several Saccharum species. Traditional breeding methods have been employed extensively in different countries over the past decades to develop varieties with increased sucrose yield and resistance to pests and diseases. Conventional variety improvement, however, may be limited by the narrow pool of suitable genes. Thus, molecular genetics is seen as a promising tool to assist in the process of developing improved varieties. The SUCEST-FUN Project (http://sucest-fun.org) aims to associate function with sugarcane genes using a variety of tools, in particular those that enable the study of the sugarcane transcriptome. An extensive analysis has been conducted to characterise, phenotypically, sugarcane genotypes with regard to their sucrose content, biomass and drought responses. Through the analysis of different cultivars, genes associated with sucrose content, yield, lignin and drought have been identified. Currently, tools are being developed to determine signalling and regulatory networks in grasses, and to sequence the sugarcane genome, as well as to identify sugarcane promoters. This is being implemented through the SUCEST-FUN (http://sucest-fun.org) and GRASSIUS databases (http://grassius.org), the cloning of sugarcane promoters, the identification of cis-regulatory elements (CRE) using Chromatin Immunoprecipitation-sequencing (ChIP-Seq) and the generation of a comprehensive Signal Transduction and Transcription gene catalogue (SUCAST Catalogue).

Modeling the Emergence of Circadian Rhythms in a Clock Neuron Network

Circadian rhythms in pacemaker cells persist for weeks in constant darkness, while in other types of cells the molecular oscillations that underlie circadian rhythms damp rapidly under the same conditions. Although much progress has been made in understanding the biochemical and cellular basis of circadian rhythms, the mechanisms leading to damped or self-sustained oscillations remain largely unknown. There exist many mathematical models that reproduce the circadian rhythms in the case of a single cell of the Drosophila fly. However, not much is known about the mechanisms leading to coherent circadian oscillation in clock neuron networks. In this work we have implemented a model for a network of interacting clock neurons to describe the emergence (or damping) of circadian rhythms in Drosophila fly, in the absence of zeitgebers. Our model consists of an array of pacemakers that interact through the modulation of some parameters by a network feedback. The individual pacemakers are described by a well-known biochemical model for circadian oscillation, to which we have added degradation of PER protein by light and multiplicative noise. The network feedback is the PER protein level averaged over the whole network. In particular, we have investigated the effect of modulation of the parameters associated with (i) the control of net entrance of PER into the nucleus and (ii) the non-photic degradation of PER. Our results indicate that the modulation of PER entrance into the nucleus allows the synchronization of clock neurons, leading to coherent circadian oscillations under constant dark condition. On the other hand, the modulation of non-photic degradation cannot reset the phases of individual clocks subjected to intrinsic biochemical noise.

Sequence and Copy Number Analyses of HEXB Gene in Patients Affected by Sandhoff Disease: Functional Characterization of 9 Novel Sequence Variants

Sandhoff disease (SD) is a lysosomal disorder caused by mutations in the HEXB gene. To date, 43 mutations of HEXB have been described, including 3 large deletions. Here, we have characterized 14 unrelated SD patients and developed a Multiplex Ligation-dependent Probe Amplification (MLPA) assay to investigate the presence of large HEXB deletions. Overall, we identified 16 alleles, 9 of which were novel, including 4 sequence variation leading to aminoacid changes [c.626C>T (p.T209I), c.634C>A (p.H212N), c.926G>T (p.C309F), c.1451G>A (p.G484E)] 3 intronic mutations (c.1082+5G>A, c.1242+1G>A, c.1169+5G>A), 1 nonsense mutation c.146C>A (p.S49X) and 1 small in-frame deletion c.1260_1265delAGTTGA (p.V421_E422del). Using the new MLPA assay, 2 previously described deletions were identified. In vitro expression studies showed that proteins bearing aminoacid changes p.T209I and p.G484E presented a very low or absent activity, while proteins bearing the p.H212N and p.C309F changes retained a significant residual activity. The detrimental effect of the 3 novel intronic mutations on the HEXB mRNA processing was demonstrated using a minigene assay. Unprecedentedly, minigene studies revealed the presence of a novel alternative spliced HEXB mRNA variant also present in normal cells. In conclusion, we provided new insights into the molecular basis of SD and validated an MLPA assay for detecting large HEXB deletions.

Gene Expression Profile in Response to Doxorubicin-Rapamycin Combined Treatment of HER-2-Overexpressing Human Mammary Epithelial Cell Lines

HER-2-positive breast cancers frequently sustain elevated AKT/mTOR signaling, which has been associated with resistance to doxorubicin treatment. Here, we investigated whether rapamycin, an mTOR inhibitor, increased the sensitivity to doxorubicin therapy in two HER-2-overexpressing cell lines: C5.2, which was derived from the parental HB4a by transfection with HER-2 and SKBR3, which exhibits HER-2 amplification. The epithelial mammary cell line HB4a was also analyzed. The combined treatment using 20 nmol/L of rapamycin and 30 nmol/L of doxorubicin arrested HB4a and C5.2 cells in S to G(2)-M, whereas SKBR3 cells showed an increase in the G(0)-G(1) phase. Rapamycin increased the sensitivity to doxorubicin in HER-2-overexpressing cells by approximately 2-fold, suggesting that the combination displayed a more effective antiproliferative action. Gene expression profiling showed that these results might reflect alterations in genes involved in canonical pathways related to purine metabolism, oxidative phosphorylation, protein ubiquitination, and mitochondrial dysfunction. A set of 122 genes modulated by the combined treatment and specifically related to HER-2 overexpression was determined by finding genes commonly regulated in both C5.2 and SKBR3 that were not affected in HB4a cells. Network analysis of this particular set showed a smaller subgroup of genes in which coexpression pattern in HB4a cells was disrupted in C5.2 and SKBR3. Altogether, our data showed a subset of genes that might be more robust than individual markers in predicting the response of HER-2-overexpressing breast cancers to doxorubicin and rapamycin combination. Mol Cancer Ther; 11(2); 464-74. (C) 2011 AACR.

DNA vaccine containing the mycobacterial hsp65 gene prevented insulitis in MLD-STZ diabetes

Abstract Background Our group previously demonstrated that a DNA plasmid encoding the mycobacterial 65-kDa heat shock protein (DNA-HSP65) displayed prophylactic and therapeutic effect in a mice model for tuberculosis. This protection was attributed to induction of a strong cellular immunity against HSP65. As specific immunity to HSP60 family has been detected in arthritis, multiple sclerosis and diabetes, the vaccination procedure with DNA-HSP65 could induce a cross-reactive immune response that could trigger or worsen these autoimmune diseases. Methods In this investigation was evaluated the effect of a previous vaccination with DNA-HSP65 on diabetes development induced by Streptozotocin (STZ). C57BL/6 mice received three vaccine doses or the corresponding empty vector and were then injected with multiple low doses of STZ. Results DNA-HSP65 vaccination protected mice from STZ induced insulitis and this was associated with higher production of IL-10 in spleen and also in the islets. This protective effect was also concomitant with the appearance of a regulatory cell population in the spleen and a decreased infiltration of the islets by T CD8+ lymphocytes. The vector (DNAv) also determined immunomodulation but its protective effect against insulitis was very discrete. Conclusion The data presented in this study encourages a further investigation in the regulatory potential of the DNA-HSP65 construct. Our findings have important implications for the development of new immune therapy strategies to combat autoimmune diseases.

Multivariate gene expression analysis reveals functional connectivity changes between normal/tumoral prostates

Abstract Background Prostate cancer is a leading cause of death in the male population, therefore, a comprehensive study about the genes and the molecular networks involved in the tumoral prostate process becomes necessary. In order to understand the biological process behind potential biomarkers, we have analyzed a set of 57 cDNA microarrays containing ~25,000 genes. Results Principal Component Analysis (PCA) combined with the Maximum-entropy Linear Discriminant Analysis (MLDA) were applied in order to identify genes with the most discriminative information between normal and tumoral prostatic tissues. Data analysis was carried out using three different approaches, namely: (i) differences in gene expression levels between normal and tumoral conditions from an univariate point of view; (ii) in a multivariate fashion using MLDA; and (iii) with a dependence network approach. Our results show that malignant transformation in the prostatic tissue is more related to functional connectivity changes in their dependence networks than to differential gene expression. The MYLK, KLK2, KLK3, HAN11, LTF, CSRP1 and TGM4 genes presented significant changes in their functional connectivity between normal and tumoral conditions and were also classified as the top seven most informative genes for the prostate cancer genesis process by our discriminant analysis. Moreover, among the identified genes we found classically known biomarkers and genes which are closely related to tumoral prostate, such as KLK3 and KLK2 and several other potential ones. Conclusion We have demonstrated that changes in functional connectivity may be implicit in the biological process which renders some genes more informative to discriminate between normal and tumoral conditions. Using the proposed method, namely, MLDA, in order to analyze the multivariate characteristic of genes, it was possible to capture the changes in dependence networks which are related to cell transformation.

Constraint-based analysis of gene interactions using restricted boolean networks and time-series data

Abstract Background A popular model for gene regulatory networks is the Boolean network model. In this paper, we propose an algorithm to perform an analysis of gene regulatory interactions using the Boolean network model and time-series data. Actually, the Boolean network is restricted in the sense that only a subset of all possible Boolean functions are considered. We explore some mathematical properties of the restricted Boolean networks in order to avoid the full search approach. The problem is modeled as a Constraint Satisfaction Problem (CSP) and CSP techniques are used to solve it. Results We applied the proposed algorithm in two data sets. First, we used an artificial dataset obtained from a model for the budding yeast cell cycle. The second data set is derived from experiments performed using HeLa cells. The results show that some interactions can be fully or, at least, partially determined under the Boolean model considered. Conclusions The algorithm proposed can be used as a first step for detection of gene/protein interactions. It is able to infer gene relationships from time-series data of gene expression, and this inference process can be aided by a priori knowledge available.

Ventral premammillary nucleus as a critical sensory relay to the maternal aggression network

Maternal aggression is under the control of a wide variety of factors that prime the females for aggression or trigger the aggressive event. Maternal attacks are triggered by the perception of sensory cues from the intruder, and here we have identified a site in the hypothalamus of lactating rats that is highly responsive to the male intruder—the ventral premammillary nucleus (PMv). The PMv is heavily targeted by the medial amygdalar nucleus, and we used lesion and immediate-early gene studies to test our working hypothesis that the PMv signals the presence of a male intruder and transfers this information to the network organizing maternal aggression. PMv-lesioned dams exhibit significantly reduced maternal aggression, without affecting maternal care. The Fos analysis revealed that PMv influences the activation of hypothalamic and septal sites shown to be mobilized during maternal aggression, including the medial preoptic nucleus (likely to represent an important locus to integrate priming stimuli critical for maternal aggression), the caudal two-thirds of the hypothalamic attack area (comprising the ventrolateral part of the ventromedial hypothalamic nucleus and the adjacent tuberal region of the lateral hypothalamic area, critical for the expression of maternal aggression), and the ventral part of the anterior bed nuclei of the stria terminalis (presently discussed as being involved in controlling neuroendocrine and autonomic responses accompanying maternal aggression). These findings reveal an important role for the PMv in detecting the male intruder and how this nucleus modulates the network controlling maternal aggression.

Morphogenesis of follicular epithelium in Drosophila melanogaster: function of von Hippel-Lindau tumour suppressor gene

During my PhD I have been involved in several projects regarding the morphogenesis of the follicular epithelium, such as the analysis of the pathways that correlate follicular epithelium patterning and eggshell genes expression. Moreover, I used the follicular epithelium as a model system to analyze the function of the Drosophila homolog of the human von Hippel-Lindau (d-VHL) during oogenesis, in order to gain insight into the role of h-VHL for the pathogenesis of VHL disease. h-VHL is implicated in a variety of processes and there is now a greater appreciation of HIF-independent h-VHL functions that are relevant to tumour development, including maintenance and organization of the primary cilium, maintenance of the differentiated phenotype in renal cells and regulation of epithelial-mesenchymal transition. However, the function of h-VHL gene during development has not been fully understood. It was previously shown that d-VHL down-regulates the motility of tubular epithelial cells (tracheal cells) during embryogenesis. Epithelial morphogenesis is important for organogenesis and pivotal for carcinogenesis, but mechanisms that control it are poorly understood. The Drosophila follicular epithelium is a genetically tractable model to understand these mechanisms in vivo. Therefore, to examine whether d-VHL has a role in epithelial morphogenesis and maintenance, I performed genetic and molecular analyses by using in vivo and in vitro approaches. From my analysis, I determined that d-VHL binds to and stabilizes microtubules. Loss of d-VHL depolymerizes the microtubule network during oogenesis, leading to a possible deregulation in the subcellular trafficking transport of polarity markers from Golgi apparatus to the different domains in which follicle cells are divided. The analysis carried out has allowed to establish a significant role of d-VHL in the maintenance of the follicular epithelium integrity.

Identification and characterization of the sRNA network in Neisseria meningitidis

Bacterial small regulatory RNAs (sRNAs) are posttranscriptional regulators involved in stress responses. These short non-coding transcripts are synthesised in response to a signal, and control gene expression of their regulons by modulating the translation or stability of the target mRNAs, often in concert with the RNA chaperone Hfq. Characterization of a Hfq knock out mutant in Neisseria meningitidis revealed that it has a pleiotropic phenotype, suggesting a major role for Hfq in adaptation to stresses and virulence and the presence of Hfq-dependent sRNA activity. Global gene expression analysis of regulated transcripts in the Hfq mutant revealed the presence of a regulated sRNA, incorrectly annotated as an open reading frame, which we renamed AniS. The synthesis of this novel sRNA is anaerobically induced through activation of its promoter by the FNR global regulator and through global gene expression analyses we identified at least two predicted mRNA targets of AniS. We also performed a detailed molecular analysis of the action of the sRNA NrrF,. We demonstrated that NrrF regulates succinate dehydrogenase by forming a duplex with a region of complementarity within the sdhDA region of the succinate dehydrogenase transcript, and Hfq enhances the binding of this sRNA to the identified target in the sdhCDAB mRNA; this is likely to result in rapid turnover of the transcript in vivo. In addition, in order to globally investigate other possible sRNAs of N. meningitdis we Deep-sequenced the transcriptome of this bacterium under both standard in vitro and iron-depleted conditions. This analysis revealed genes that were actively transcribed under the two conditions. We focused our attention on the transcribed non-coding regions of the genome and, along with 5’ and 3’ untranslated regions, 19 novel candidate sRNAs were identified. Further studies will be focused on the identification of the regulatory networks of these sRNAs, and their targets.

Approccio network-based alla discriminant analysis mediante HPC per la ricerca di signature ottimali in dati ad alta dimensionalità

Il presente lavoro di tesi si inserisce nell’ambito della classificazione di dati ad alta dimensionalità, sviluppando un algoritmo basato sul metodo della Discriminant Analysis. Esso classifica i campioni attraverso le variabili prese a coppie formando un network a partire da quelle che hanno una performance sufficientemente elevata. Successivamente, l’algoritmo si avvale di proprietà topologiche dei network (in particolare la ricerca di subnetwork e misure di centralità di singoli nodi) per ottenere varie signature (sottoinsiemi delle variabili iniziali) con performance ottimali di classificazione e caratterizzate da una bassa dimensionalità (dell’ordine di 101, inferiore di almeno un fattore 103 rispetto alle variabili di partenza nei problemi trattati). Per fare ciò, l’algoritmo comprende una parte di definizione del network e un’altra di selezione e riduzione della signature, calcolando ad ogni passaggio la nuova capacità di classificazione operando test di cross-validazione (k-fold o leave- one-out). Considerato l’alto numero di variabili coinvolte nei problemi trattati – dell’ordine di 104 – l’algoritmo è stato necessariamente implementato su High-Performance Computer, con lo sviluppo in parallelo delle parti più onerose del codice C++, nella fattispecie il calcolo vero e proprio del di- scriminante e il sorting finale dei risultati. L’applicazione qui studiata è a dati high-throughput in ambito genetico, riguardanti l’espressione genica a livello cellulare, settore in cui i database frequentemente sono costituiti da un numero elevato di variabili (104 −105) a fronte di un basso numero di campioni (101 −102). In campo medico-clinico, la determinazione di signature a bassa dimensionalità per la discriminazione e classificazione di campioni (e.g. sano/malato, responder/not-responder, ecc.) è un problema di fondamentale importanza, ad esempio per la messa a punto di strategie terapeutiche personalizzate per specifici sottogruppi di pazienti attraverso la realizzazione di kit diagnostici per l’analisi di profili di espressione applicabili su larga scala. L’analisi effettuata in questa tesi su vari tipi di dati reali mostra che il metodo proposto, anche in confronto ad altri metodi esistenti basati o me- no sull’approccio a network, fornisce performance ottime, tenendo conto del fatto che il metodo produce signature con elevate performance di classifica- zione e contemporaneamente mantenendo molto ridotto il numero di variabili utilizzate per questo scopo.

Kaiso und CTCF regulieren geprägte Gene in cis und in trans

Geprägte Gene besitzen die Besonderheit, dass sie jeweils nur von einem Allel exprimiert werden und in der Regel in Imprinting Clustern (ICs) im Genom vorliegen. Bei der Regulation in solchen ICs spielen differentiell methylierte Imprinting Kontrollregionen (ICRs) und dort stattfindende Proteinbindungen eine wichtige Rolle. Die essentielle Bedeutung der CTCF-Bindung an die ICR1 in 11p15.5 für die Expressionsregulation der geprägten Gene H19 und IGF2 ist bereits bekannt. In der vorliegenden Arbeit sollte die Bindung von Kaiso an die unmethylierte ICR1 bei humanen Zellen mit maternaler uniparentaler Disomie von 11p15 (upd(11p15)mat) nachgewiesen und die genaue Bindungsverteilung von Kaiso und CTCF in den B-Repeats der Kontrollregion bestimmt werden. Cis-regulatorische und chromosomenübergreifende transkriptionelle Effekte der ICR1-Proteinbindungen sollten dann durch qPCR-Analysen geprägter Gene bei Zellen mit maternaler und paternaler upd(11p15) und nach siRNA-basierter Herunterregulation der beiden Proteine in Zellen mit upd(11p15)mat analysiert werden. In der vorliegenden Arbeit konnte erstmals gezeigt werden, dass Kaiso an die unmethylierte ICR1 bindet. Dabei kann zumindest von einer Bindestellennutzung in der distalen ICR1-Hälfte ausgegangen werden. Für CTCF hingegen wurde eine Nutzung aller analysierten Repeats in beiden ICR1-Hälften gefunden. In der maternalen bzw. paternalen upd(11p15) entspricht die Expression der 11p15.5-Gene IGF2, H19, CDKN1C und KCNQ1OT1 dem jeweiligen Disomie-Status. Von den nicht auf Chromosom 11 gelegenen geprägten Genen zeigen MEST und PLAGL1 bei Zellen mit upd(11p15)pat sowie PEG3 und GRB10 bei der upd(11p15)mat eine stärkere Expression. Ein CTCF-knockdown in Zellen mit upd(11p15)mat führt zur IGF2-Expressionssteigerung. Dies tritt in noch stärkerem Maße beim knockdown von Kaiso auf, wobei hier zusätzlich eine gesteigerte Expression von H19 vorliegt. Des Weiteren findet man beim CTCF-knockdown einen MEST-Expressionsanstieg und beim Kaiso-knockdown gesteigerte Expressionen der Gene PEG3, GRB10 und PLAGL1. Damit lassen sich sowohl eigenständige cis-regulatorische Effekte der ICR1-Bindung beider Proteine auf geprägte Gene des IC1 als auch chromosomenübergreifende Effekte erkennen. Vor allem die starken H19-Expressionsanstiege beim Kaiso-knockdown treten korrelierend mit Veränderungen von geprägten Genen anderer Chromosomen auf. Damit unterstützen die Daten die Theorie, dass die Expressionsregulation geprägter Gene koordiniert in einer Art Netzwerk stattfinden könnte und dabei bestimmte Faktoren wie H19 und PLAGL1 eine übergeordnete Regulatorfunktion besitzen, wie es in Vergangenheit in der Maus beschrieben wurde. Die Expressionsanalysen von PLAGL1 und MEST deuten darüber hinaus durch ihre tendenziell übereinstimmenden Werte bei der paternalen upd mit hypermethylierter ICR1 und den knockdowns auf die Existenz von Chromatin-Interaktionen zwischen der ICR1 und Abschnitten auf den Chromosomen 6 und 7 hin, ggf. mit einem entsprechenden lokalen Effekt der Proteine in diesen Loci. Proteinbindungen an die maternale ICR1 scheinen damit sowohl cis-regulatorisch die Transkription der geprägten Gene IGF2 und H19 zu beeinflussen als auch durch die H19-Expression ein funktionelles Netzwerk geprägter Gene als trans-Faktor zu regulieren und für Interaktionen zwischen verschiedenen Chromosomen mit transkriptionsregulierender Wirkung verantwortlich zu sein.

Targeting neuronal populations by AAV-mediated gene transfer for studying the endocannabinoid system

The cannabinoid type 1 (CB1) receptor is involved in a plethora of physiological functions and heterogeneously expressed on different neuronal populations. Several conditional loss-of-function studies revealed distinct effects of CB1 receptor signaling on glutamatergic and GABAergic neurons, respectively. To gain a comprehensive picture of CB1 receptor-mediated effects, the present study aimed at developing a gain-of-function approach, which complements conditional loss-of-function studies. Therefore, adeno-associated virus (AAV)-mediated gene delivery and Cre-mediated recombination were combined to recreate an innovative method, which ensures region- and cell type-specific transgene expression in the brain. This method was used to overexpress the CB1 receptor in glutamatergic pyramidal neurons of the mouse hippocampus. Enhanced CB1 receptor activity at glutamatergic terminals caused impairment in hippocampus-dependent memory performance. On the other hand, elevated CB1 receptor levels provoked an increased protection against kainic acid-induced seizures and against excitotoxic neuronal cell death. This finding indicates the protective role of CB1 receptor on hippocampal glutamatergic terminals as a molecular stout guard in controlling excessive neuronal network activity. Hence, CB1 receptor on glutamatergic hippocampal neurons may represent a target for novel agents to restrain excitotoxic events and to treat neurodegenerative diseases. Endocannabinoid synthesizing and degrading enzymes tightly regulate endocannabinoid signaling, and thus, represent a promising therapeutic target. To further elucidate the precise function of the 2-AG degrading enzyme monoacylglycerol lipase (MAGL), MAGL was overexpressed specifically in hippocampal pyramidal neurons. This genetic modification resulted in highly increased MAGL activity accompanied by a 50 % decrease in 2-AG levels without affecting the content of arachidonic acid and anandamide. Elevated MAGL protein levels at glutamatergic terminals eliminated depolarization-induced suppression of excitation (DSE), while depolarization-induced suppression of inhibition (DSI) was unchanged. This result indicates that the on-demand availability of the endocannabinoid 2-AG is crucial for short-term plasticity at glutamatergic synapses in the hippocampus. Mice overexpressing MAGL exhibited elevated corticosterone levels under basal conditions and an increase in anxiety-like behavior, but surprisingly, showed no changes in aversive memory formation and in seizure susceptibility. This finding suggests that 2 AG-mediated hippocampal DSE is essential for adapting to aversive situations, but is not required to form aversive memory and to protect against kainic acid-induced seizures. Thus, specific inhibition of MAGL expressed in hippocampal pyramidal neurons may represent a potential treatment strategy for anxiety and stress disorders. Finally, the method of AAV-mediated cell type-specific transgene expression was advanced to allow drug-inducible and reversible transgene expression. Therefore, elements of the tetracycline-controlled gene expression system were incorporated in our “conditional” AAV vector. This approach showed that transgene expression is switched on after drug application and that background activity in the uninduced state was only detectable in scattered cells of the hippocampus. Thus, this AAV vector will proof useful for future research applications and gene therapy approaches.

Clinical, polysomnographic and genome-wide association analyses of narcolepsy with cataplexy: a European Narcolepsy Network study

The aim of this study was to describe the clinical and PSG characteristics of narcolepsy with cataplexy and their genetic predisposition by using the retrospective patient database of the European Narcolepsy Network (EU-NN). We have analysed retrospective data of 1099 patients with narcolepsy diagnosed according to International Classification of Sleep Disorders-2. Demographic and clinical characteristics, polysomnography and multiple sleep latency test data, hypocretin-1 levels, and genome-wide genotypes were available. We found a significantly lower age at sleepiness onset (men versus women: 23.74 ± 12.43 versus 21.49 ± 11.83, P = 0.003) and longer diagnostic delay in women (men versus women: 13.82 ± 13.79 versus 15.62 ± 14.94, P = 0.044). The mean diagnostic delay was 14.63 ± 14.31 years, and longer delay was associated with higher body mass index. The best predictors of short diagnostic delay were young age at diagnosis, cataplexy as the first symptom and higher frequency of cataplexy attacks. The mean multiple sleep latency negatively correlated with Epworth Sleepiness Scale (ESS) and with the number of sleep-onset rapid eye movement periods (SOREMPs), but none of the polysomnographic variables was associated with subjective or objective measures of sleepiness. Variant rs2859998 in UBXN2B gene showed a strong association (P = 1.28E-07) with the age at onset of excessive daytime sleepiness, and rs12425451 near the transcription factor TEAD4 (P = 1.97E-07) with the age at onset of cataplexy. Altogether, our results indicate that the diagnostic delay remains extremely long, age and gender substantially affect symptoms, and that a genetic predisposition affects the age at onset of symptoms.