Loss of the Chr16p11.2 ASD candidate gene QPRT leads to aberrant neuronal differentiation in the SH-SY5Y neuronal cell model

Background: Altered neuronal development is discussed as the underlying pathogenic mechanism of autism spectrum disorders (ASD). Copy number variations of 16p11.2 have recurrently been identified in individuals with ASD. Of the 29 genes within this region, quinolinate phosphoribosyltransferase (QPRT) showed the strongest regulation during neuronal differentiation of SH-SY5Y neuroblastoma cells. We hypothesized a causal relation between this tryptophan metabolism-related enzyme and neuronal differentiation. We thus analyzed the effect of QPRT on the differentiation of SH-SY5Y and specifically focused on neuronal morphology, metabolites of the tryptophan pathway, and the neurodevelopmental transcriptome. Methods: The gene dosage-dependent change of QPRT expression following Chr16p11.2 deletion was investigated in a lymphoblastoid cell line (LCL) of a deletion carrier and compared to his non-carrier parents. Expression of QPRT was tested for correlation with neuromorphology in SH-SY5Y cells. QPRT function was inhibited in SH-SY5Y neuroblastoma cells using (i) siRNA knockdown (KD), (ii) chemical mimicking of loss of QPRT, and (iii) complete CRISPR/Cas9-mediated knock out (KO). QPRT-KD cells underwent morphological analysis. Chemically inhibited and QPRT-KO cells were characterized using viability assays. Additionally, QPRT-KO cells underwent metabolite and whole transcriptome analyses. Genes differentially expressed upon KO of QPRT were tested for enrichment in biological processes and co-regulated gene-networks of the human brain. Results: QPRT expression was reduced in the LCL of the deletion carrier and significantly correlated with the neuritic complexity of SH-SY5Y. The reduction of QPRT altered neuronal morphology of differentiated SH-SY5Y cells. Chemical inhibition as well as complete KO of the gene were lethal upon induction of neuronal differentiation, but not proliferation. The QPRT-associated tryptophan pathway was not affected by KO. At the transcriptome level, genes linked to neurodevelopmental processes and synaptic structures were affected. Differentially regulated genes were enriched for ASD candidates, and co-regulated gene networks were implicated in the development of the dorsolateral prefrontal cortex, the hippocampus, and the amygdala. Conclusions: In this study, QPRT was causally related to in vitro neuronal differentiation of SH-SY5Y cells and affected the regulation of genes and gene networks previously implicated in ASD. Thus, our data suggest that QPRT may play an important role in the pathogenesis of ASD in Chr16p11.2 deletion carriers

Integrative bioinformatics pipeline for genome-wide association studies in neuropsychiatry and the subsequent application in Autism Spectrum Disorder cohorts

Neuropsychiatric disorders are complex, highly heritable but incompletely understood disorders. The clinical and genetic heterogeneity of these disorders poses a significant challenge to the identification of disorder related biomarkers. Besides significant progress in unveiling the genetic basis of these disorders, the underlying causes and biological mechanisms remain obscure. With the advancement in the array, sequencing, and big data technologies, a huge amount of data is generated from individuals across different platforms and in various data structures. But there is a paucity of bioinformatics tools that can integrate this plethora of data. Therefore, there is a need to develop an integrative bioinformatics data analysis tool that combines biological and clinical data from different data types to better understand the underlying genetics. This thesis presents a bioinformatics pipeline implementing data from different platforms to provide a thorough understanding of the genetic etiology of a neuropsychiatric quantitative as well as a qualitative trait of interest. Throughout the thesis, we present two aspects: one is the development and architecture of the bioinformatics pipeline named MApping the Genetics of neuropsychiatric traits to the molecular NETworks of the human brain (MAGNET). The other part demonstrates the implementation and usefulness of MAGNET analysing large Autism Spectrum Disorder (ASD) cohorts. MAGNET is a freely available command-line tool available on GitHub (https://github.com/SheenYo/MAGNET). It is implemented within one framework using data integration approaches based on state-of-the-art algorithms and software to ultimately identify the genes and pathways genetically associated with a trait of interest. MAGNET provides an edge over the existing tools since it performs a comprehensive analysis taking care of the data handling and parsing steps necessary to communicate between the different APIs (Application Program Interface). Thus, this avoids the in-between data handling steps required by researchers to provide output from one analysis to the next. Moreover, depending on the size of the dataset users can deduce important information regarding their trait of interest within a time frame of a few days. Besides gaining insights into genetic associations, one of the central features is the mapping of the associated genes onto developing human brain implementing transcriptome data of 16 different brain regions starting from the 5th post-conceptional week to over 40 years of age. In the second part as proof of concept, we implemented MAGNET on two ASD cohorts. ASD is a group of psychiatric disorders. Clinically, ASD is characterized by the following psychopathology: A) limitations in social interaction and communication, and B) restricted, repetitive behavior. The etiology of this disorder is extremely complex due to its heterogeneous clinical traits and genetics. Therefore, to date, no reliable biomarkers are identified. Here, the aim is to characterize the genetic architecture of ASD taking into account the two aforementioned ASD diagnostic domains. As well as to investigate if these domains are genetically linked or independent of each other. Moreover, we addressed the question if these traits share genetic risk with the categorical diagnosis of ASD and how much of the phenotypic variance of these traits can be explained by the underlying genetics. We included affected individuals from two ASD cohorts, i.e. the Autism Genome Project (AGP) and a German cohort consisting of 2,735 and 705 families respectively. MAGNET was applied to each of the ASD subdomains as a quantitative dependent variable. MAGNET is divided into five main sections i.e. (1) quality check of the genotype data, (2) imputation of missing genotype data, (3) association analysis of genotype and trait data, (4) gene-based analysis, and (5) enrichment analysis using gene expression data from the human brain. MAGNET was applied to each of the individual traits in each cohort to perform quality control of the genetic data and imputed the missing data in an automated fashion. MAGNET identified 292 known and new ASD risk genes. These genes were subsequently assigned to biological signaling pathways and gene ontologies via MAGNET. The underlying biological mechanisms converged with respect to neuronal transmission and development processes. By reconciling these genes with the transcriptome of the developing human brain, MAGNET was able to identify that the significant genes associated with the subdomains are expressed at specific time points in brain areas such as the hippocampus, amygdala, and cortical regions. Further, we found that ASD subdomains related to domain A but not to domain B have a shared genetic etiology

Decentralized and centralized exchanges: which digital tokens pose a greater contagion risk?

This study explores the impact of trading activity on both centralized exchanges (CEXs) and decentralized exchanges (DEXs) on information transmission patterns between digital and traditional investment assets. Utilizing a quantile connectedness approach, we analyze the relationships among DEX tokens, CEX tokens, and various assets, including Gold, Oil, Bitcoin, REITs, Equity, Bonds, and the US dollar index. Our results reveal that in the lowest quantile, DEXand CEX tokens primarily receive spillovers, while other assets act as the main transmitters. In contrast, in the upper quantile, DEX and CEX tokens become the primary transmitters of spillovers to other assets. These findings hold significant implications for financial portfolio management, as they demonstrate that during a short squeeze period, DEX-CEX tokens exhibit contagious effects on other assets, diminishing the effectiveness of risk management and portfolio strategies.Furthermore, our study suggests that DEX-CEX tokens serve as optimal hedges for oil, offering a cost-effective alternative for hedging Gold and the USD Index

Connectedness between travel & tourism tokens, tourism equity, and other assets

We examine the return and volatility connectedness between travel & tourism tokens and other financial assets, including travel and tourism stocks, energy (WTI oil), cryptocurrency (bitcoin) and bonds, gold, the US dollar, using a generalized vector autoregressive framework. Findings show, in normal economic periods, only weak static spillovers between travel & tourism tokens and other assets. However, dynamic analysis reveals increased intensity of spillovers between travel & tourism tokens and other assets during COVID-19. Results are consistent with travel & tourism tokens offering diversification, including surprisingly to equity of the travel and tourism industry, during downturns that particularly impact tourism

Differenzierung von Angststörungen im Elternurteil : Untersuchung anhand des Fragebogens für Angst- und Zwangsstörungen (FBB-ANZ)

Im Rahmen der Abklärung des Verdachts einer Angststörung kommen in der klinischen Praxis regelmäßig Screeningfrage- bögen für Eltern zum Einsatz, die teilweise auch unterschiedliche Angststörungen erfassen. Im klinischen Kontext ist die valide Abgrenzung von Angststörungen zu anderen psychischen Störung sowie die differenzialdiagnostische Abklärung spezifischer Angststörungen relevant. Das Ziel der vorliegenden Studie ist die Untersuchung der Validität eines Screenings durch den Fremdbeurteilungsbogen für Angst- und Zwangsstörun- gen (FBB-ANZ) hinsichtlich unterschiedlicher Angststörungen. Überprüft wurde die Diskriminationsfähigkeit von (1) Angststörungen und ande- ren kinder- und jugendpsychiatrischen Störungen und (2) verschiedenen Angststörungen mittels ROC-Analysen (Receiver Operating Characte- ristics). Der FBB-ANZ wurde von 972 Eltern von 4;00–11;11-jährigen Kindern und 12;00–17;11-jährigen Jugendlichen mit Angststörungen oder depressiven Episoden oder externalisierenden Störungen ausgefüllt. Die Diskriminationsfähigkeit von Angststörungen und externalisierenden Störungen bei Kindern (AUC [Area Under the Curve] = .72) und Jugendlichen (AUC = .76) sowie von Angststörungen und depressiven Episoden im Kindesalter (AUC = .77) war moderat. Eine gute Unterscheidung verschiedener Angststörungen bei Angstpatient_innen war nur hinsichtlich der emotionalen Störung mit Trennungsangst bei Kindern (AUC = .84) und Jugendlichen (AUC = .87) gegeben. Die Ergebnisse deuten auf einen eingeschränkten diagnostischen Nutzen des Screeningurteils der Eltern zur Unterscheidung verschiedener Angststörungen im Kindes- und Jugendalter hin. Mögliche Erklärungsansätze für die vorliegenden Ergebnisse werden kritisch diskutiert.Parent ratings are often used for screening during the diagnostic evaluation of anxiety disorders. Clinically, it is important to correctly differentiate between anxiety and other psychiatric disorders and to distinguish specific anxiety disorders. The present study examined the validity of the screening results obtained by the Parent Questionnaire for Anxiety and Obsessive-Compulsive Disorders (FBB-ANZ). We exam- ined whether the FBB-ANZ discriminated (1) anxiety and other psychiatric disorders and (2) specific anxiety disorders in children and adoles- cents using ROC analyses. 972 parents of 4;00–11;11-year-old children and 12;00–17;11-year-old adolescents with anxiety disorders, depres- sive episodes, or externalizing disorders completed the FBB-ANZ. Discrimination of anxiety disorders and externalizing disorders in children (AUC = .72) and adolescents (AUC = .76) as well as depressive episodes in children (AUC = .77) was moderate. Good discrimination of different anxiety disorders was found only for separation anxiety in children (AUC = .84) and adolescents (AUC = .87). The results indicate the limited di- agnostic benefit of parent ratings for discriminating different anxiety disorders in children and adolescents. Potential explanations for the re- sults are critically discussed

Genetic risk factors and their infl uence on neural development in autism spectrum disorders

Die Ätiologie der Autismus-Spektrum-Störungen (ASS) ist in genetischen Risikofaktoren sowie der Interaktion von genetischen und biologisch wirksamen Umweltrisikofaktoren begründet. ASS werden aufgrund von Verhaltensmerkmalen, nämlich bleibend eingeschränkter sozialer Kommunikation, sowie durch stereotypes Verhalten, sensorische und Sonderinteressen diagnostiziert. Hinsichtlich des genetischen Hintergrundes besteht eine hohe genetische Heterogenität, d. h., die genetischen Ursachen sind vielfältig und individuell oft sehr unterschiedlich ausgeprägt. Allerdings konvergieren diese Ursachen in bestimmten biologischen Mechanismen und überlappenden biologischen Endstrecken, deren Veränderung sehr wahrscheinlich den autismusspezifischen Verhaltensmerkmalen zugrunde liegt. Die vorliegende, selektive Literaturübersicht summiert die genetischen Befunde und fokusiert sich insbesondere auf Mechanismen und Endstrecken, die aufgrund der neueren Forschung immer besser charakterisiert werden. Der Artikel schließt mit Hinweisen zur klinischen Relevanz der aktuellen Befunde sowie offenen Fragen der translationalen Forschung.Autism spectrum disorders are etiologically based on genetic and specific gene x biologically relevant environmental risk factors. They are diagnosed based on behavioral characteristics, such as impaired social communication and stereotyped, repetitive behavior and sensory as well as special interests. The genetic background is heterogeneous, i. e., it comprises diverse genetic risk factors across the disorder and high interindividual differences of specific genetic risk factors. Nevertheless, risk factors converge regarding underlying biological mechanisms and shared pathways, which likely cause the autism-specific behavioral characteristics. The current selective literature review summarizes differential genetic risk factors and focuses particularly on mechanisms and pathways currently being discussed by international research. In conclusion, clinically relevant aspects and open translational research questions are presented

Co-Inflammatory Roles of TGFβ1 in the Presence of TNFα Drive a Pro-inflammatory Fate in Mesenchymal Stem Cells

High plasticity is a hallmark of mesenchymal stem cells (MSCs), and as such, their differentiation and activities may be shaped by factors of their microenvironment. Bones, tumors, and cardiomyopathy are examples of niches and conditions that contain MSCs and are enriched with tumor necrosis factor α (TNFα) and transforming growth factor β1 (TGFβ1). These two cytokines are generally considered as having opposing roles in regulating immunity and inflammation (pro- and anti-inflammatory, respectively). Here, we performed global gene expression analysis of human bone marrow-derived MSCs and identified overlap in half of the transcriptional programs that were modified by TNFα and TGFβ1. The two cytokines elevated the mRNA expression of soluble factors, including mRNAs of pro-inflammatory mediators. Accordingly, the typical pro-inflammatory factor TNFα prominently induced the protein expression levels of the pro-inflammatory mediators CCL2, CXCL8 (IL-8), and cyclooxygenase-2 (Cox-2) in MSCs, through the NF-κB/p65 pathway. In parallel, TGFβ1 did not elevate CXCL8 protein levels and induced the protein expression of CCL2 at much lower levels than TNFα; yet, TGFβ1 readily induced Cox-2 and acted predominantly via the Smad3 pathway. Interestingly, combined stimulation of MSCs by TNFα + TGFβ1 led to a cooperative induction of all three inflammatory mediators, indicating that TGFβ1 functioned as a co-inflammatory cytokine in the presence of TNFα. The cooperative activities of TNFα + TGFβ1 that have led to CCL2 and CXCL8 induction were almost exclusively dependent on p65 activation and were not regulated by Smad3 or by the upstream regulator TGFβ-activated kinase 1 (TAK1). In contrast, the TNFα + TGFβ1-induced cooperative elevation in Cox-2 was mostly dependent on Smad3 (demonstrating cooperativity with activated NF-κB) and was partly regulated by TAK1. Studies with MSCs activated by TNFα + TGFβ1 revealed that they release factors that can affect other cells in their microenvironment and induce breast tumor cell elongation, migration, and scattering out of spheroid tumor masses. Thus, our findings demonstrate a TNFα + TGFβ1-driven pro-inflammatory fate in MSCs, identify specific molecular mechanisms involved, and propose that TNFα + TGFβ1-stimulated MSCs influence the tumor niche. These observations suggest key roles for the microenvironment in regulating MSC functions, which in turn may affect different health-related conditions

Cytopathological evaluation of thyroid by fine needle aspiration cytology and its association with thyroid function

Introduction: Fine needle aspiration cytology is a reliable method for thyroid nodule evaluation (FNAC). Thyroid nodules often cause abnormal thyroid function tests, which are used for diagnosis and therapy. Thyroid cancer and incorrect thyroid function testing are still debated. Objective: We aimed to evaluate the cytopathological features of thyroid nodules by FNAC and their association with thyroid function tests. Methods: This 12-month cross-sectional study was conducted in Peshawar, Pakistan. 350 thyroid nodule patients were referred to endocrinology. All research participants had a physical checkup and thyroid function testing. Thyroid function testing measured TSH and FT4 using conventional laboratory procedures. All individuals had 23-gauge ultrasound-guided thyroid nodule FNAC. Pathologists used the Bethesda System for Reporting Thyroid Cytopathology to evaluate FNAC samples. SPSS 25 analyzed the data. Descriptive statistics detailed the study population's clinical and demographic characteristics. Logistic regression was utilized to examine the relationship between thyroid function tests and thyroid cancer risk and FNAC's thyroid cancer detection effectiveness. Results: For this research, a total of 350 thyroid nodule patients were included having the median age 39.8 (20-60) years and the ratio of female to male participants was 3:1.&nbsp