82 research outputs found

    PAK1 Protein Expression in the Auditory Cortex of Schizophrenia Subjects

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    Deficits in auditory processing are among the best documented endophenotypes in schizophrenia, possibly due to loss of excitatory synaptic connections. Dendritic spines, the principal post-synaptic target of excitatory projections, are reduced in schizophrenia. p21-activated kinase 1 (PAK1) regulates both the actin cytoskeleton and dendritic spine density, and is a downstream effector of both kalirin and CDC42, both of which have altered expression in schizophrenia. This study sought to determine if there is decreased auditory cortex PAK1 protein expression in schizophrenia through the use of quantitative western blots of 25 schizophrenia subjects and matched controls. There was no significant change in PAK1 level detected in the schizophrenia subjects in our cohort. PAK1 protein levels within subject pairs correlated positively with prior measures of total kalirin protein in the same pairs. PAK1 level also correlated with levels of a marker of dendritic spines, spinophilin. These latter two findings suggest that the lack of change in PAK1 level in schizophrenia is not due to limited sensitivity of our assay to detect meaningful differences in PAK1 protein expression. Future studies are needed to evaluate whether alterations in PAK1 phosphorylation states, or alterations in protein expression of other members of the PAK family, are present in schizophrenia

    High frequency of known copy number abnormalities and maternal duplication 15q11-q13 in patients with combined schizophrenia and epilepsy

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    <p>Abstract</p> <p>Background</p> <p>Many copy number variants (CNVs) are documented to be associated with neuropsychiatric disorders, including intellectual disability, autism, epilepsy, schizophrenia, and bipolar disorder. Chromosomal deletions of 1q21.1, 3q29, 15q13.3, 22q11.2, and <it>NRXN1 </it>and duplications of 15q11-q13 (maternal), 16p11, and 16p13.3 have the strongest association with schizophrenia. We hypothesized that cases with both schizophrenia and epilepsy would have a higher frequency of disease-associated CNVs and would represent an enriched sample for detection of other mutations associated with schizophrenia.</p> <p>Methods</p> <p>We used array comparative genomic hybridization (CGH) to analyze 235 individuals with both schizophrenia and epilepsy, 80 with bipolar disorder and epilepsy, and 191 controls.</p> <p>Results</p> <p>We detected 10 schizophrenia plus epilepsy cases in 235 (4.3%) with the above mentioned CNVs compared to 0 in 191 controls (p = 0.003). Other likely pathological findings in schizophrenia plus epilepsy cases included 1 deletion 16p13 and 1 duplication 7q11.23 for a total of 12/235 (5.1%) while a possibly pathogenic duplication of 22q11.2 was found in one control for a total of 1 in 191 (0.5%) controls (p = 0.008). The rate of abnormality in the schizophrenia plus epilepsy of 10/235 for the more definite CNVs compares to a rate of 75/7336 for these same CNVs in a series of unselected schizophrenia cases (p = 0.0004).</p> <p>Conclusion</p> <p>We found a statistically significant increase in the frequency of CNVs known or likely to be associated with schizophrenia in individuals with both schizophrenia and epilepsy compared to controls. We found an overall 5.1% detection rate of likely pathological findings which is the highest frequency of such findings in a series of schizophrenia patients to date. This evidence suggests that the frequency of disease-associated CNVs in patients with both schizophrenia and epilepsy is significantly higher than for unselected schizophrenia.</p

    Association Testing Of Copy Number Variants in Schizophrenia and Autism Spectrum Disorders

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    Background: Autism spectrum disorders and schizophrenia have been associated with an overlapping set of copynumber variant loci, but the nature and degree of overlap in copy number variants (deletions compared toduplications) between these two disorders remains unclear.Methods: We systematically evaluated three lines of evidence: (1) the statistical bases for associations of autismspectrum disorders and schizophrenia with a set of the primary CNVs thus far investigated, from previous studies;(2) data from case series studies on the occurrence of these CNVs in autism spectrum disorders, especially amongchildren, and (3) data on the extent to which the CNVs were associated with intellectual disability anddevelopmental, speech, or language delays. We also conducted new analyses of existing data on these CNVs inautism by pooling data from seven case control studies.Results: Four of the CNVs considered, dup 1q21.1, dup 15q11-q13, del 16p11.2, and dup 22q11.21, showed clearstatistical evidence as autism risk factors, whereas eight CNVs, del 1q21.1, del 3q29, del 15q11.2, del 15q13.3, dup16p11.2, dup 16p13.1, del 17p12, and del 22q11.21, were strongly statistically supported as risk factors forschizophrenia. Three of the CNVs, dup 1q21.1, dup 16p11.2, and dup 16p13.1, exhibited statistical support as riskfactors for both autism and schizophrenia, although for each of these CNVs statistical significance was nominal fortests involving one of the two disorders. For the CNVs that were statistically associated with schizophrenia but werenot statistically associated with autism, a notable number of children with the CNVs have been diagnosed withautism or ASD; children with these CNVs also demonstrate a high incidence of intellectual disability anddevelopmental, speech, or language delays.Conclusions: These findings suggest that although CNV loci notably overlap between autism and schizophrenia,the degree of strongly statistically supported overlap in specific CNVs at these loci remains limited. These analysesalso suggest that relatively severe premorbidity to CNV-associated schizophrenia in children may sometimes bediagnosed as autism spectrum disorder

    Organic pollutants in sea-surface microlayer and aerosol in thecoastal environment of Leghorn—(Tyrrhenian Sea)

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    The levels of dissolved and particle-associated n-alkanes, alkylbenzenes, phthalates, PAHs, anionic surfactants and surfactant fluorescent organic matter ŽSFOM. were measured in sea-surface microlayer ŽSML. and sub-surface water ŽSSL. samples collected in the Leghorn marine environment in September and October 1999. Nine stations, located in the Leghorn harbour and at increasing distances from the Port, were sampled three times on the same day. At all the stations, SML concentrations of the selected organic compounds were significantly higher than SSL values and the enrichment factors ŽEFsSML concentrationrSSL concentration. were greater in the particulate phase than in the dissolved phase. SML concentrations varied greatly among the sampling sites, the highest levels Žn-alkanes 3674 mgrl, phthalates 177 mgrl, total PAHs 226 mgrl. being found in the particulate phase in the Leghorn harbour. To improve the knowledge on pollutant exchanges between sea-surface waters and atmosphere, the validity of spray drop adsorption model ŽSDAM. was verified for SFOM, surface-active agents, such as phthalates, and compounds which can interact with SFOM, such as n-alkanes and PAHs. q2001 Elsevier Science B.V. All rights reserved

    The PHR proteins: intracellular signaling hubs in neuronal development and axon degeneration

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    Microbiome to Brain:Unravelling the Multidirectional Axes of Communication

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    The gut microbiome plays a crucial role in host physiology. Disruption of its community structure and function can have wide-ranging effects making it critical to understand exactly how the interactive dialogue between the host and its microbiota is regulated to maintain homeostasis. An array of multidirectional signalling molecules is clearly involved in the host-microbiome communication. This interactive signalling not only impacts the gastrointestinal tract, where the majority of microbiota resides, but also extends to affect other host systems including the brain and liver as well as the microbiome itself. Understanding the mechanistic principles of this inter-kingdom signalling is fundamental to unravelling how our supraorganism function to maintain wellbeing, subsequently opening up new avenues for microbiome manipulation to favour desirable mental health outcome
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