Association between PTGS2 polymorphism and autism spectrum disorders in Korean trios

Abnormal Microglial Density and Morphology in the Brain of Cyclooxygenase 2 Knockin Mice

Prostaglandin E2 (PGE2) is a signaling molecule produced by cyclooxygenase-2 (COX-2) that is important in healthy brain development. Anomalies in the COX-2/PGE2 pathway due to genetic or environmental factors have been linked to Autism Spectrum Disorders (ASD). Our previous studies showed that COX-2 deficient (COX-2-KI) mice exhibit sex-dependent molecular changes in the brain and associated autism-related behaviors. Here, we aim to determine the effect of COX-2-KI on microglial density and morphology in the developing brain. Microglia normally transition between an amoeboid or ramified morphology depending on their surroundings and are important for the development of the healthy brain, assisting with synaptogenesis, synaptic pruning, and phagocytosis. We use COX-2-KI male and female mice to evaluate microglia density, morphology, and branch length and number in five brain regions (cerebellum, hippocampus, olfactory bulb, prefrontal cortex, and thalamus) at the gestational day 19 (G19) and postnatal day 25 (PN25). We discovered that COX2-KI females were affected at G19 with increased microglial density, altered percentage of amoeboid and ramified microglia, affected branch length, and decreased branching networks in a region-specific manner; these effects persisted to PN25 in select regions. Interestingly, while limited changes were found in G19 COX-2-KI males, at PN25 we found increased microglial density, higher percentages of ramified microglia, and increased branch counts, and length observed in nearly all brain regions tested. Overall, we show for the first time that the COX-2 deficiency in our ASD mouse model influences microglia morphology in a sex- and region- and stage-dependent manner.

Therapeutic modulation of JAK-STAT, mTOR, and PPAR-γ signaling in neurological dysfunctions

The cytokine-activated Janus kinase (JAK)-signal transducer and activator of transcription (STAT) cascade is a pleiotropic pathway that involves receptor subunit multimerization. The mammalian target of rapamycin (mTOR) is a ubiquitously expressed serine-threonine kinase that perceives and integrates a variety of intracellular and environmental stimuli to regulate essential activities such as cell development and metabolism. Peroxisome proliferator-activated receptor-gamma (PPARγ) is a prototypical metabolic nuclear receptor involved in neural differentiation and axon polarity. The JAK-STAT, mTOR, and PPARγ signaling pathways serve as a highly conserved signaling hub that coordinates neuronal activity and brain development. Additionally, overactivation of JAK/STAT, mTOR, and inhibition of PPARγ signaling have been linked to various neurocomplications, including neuroinflammation, apoptosis, and oxidative stress. Emerging research suggests that even minor disruptions in these cellular and molecular processes can have significant consequences manifested as neurological and neuropsychiatric diseases. Of interest, target modulators have been proven to alleviate neuronal complications associated with acute and chronic neurological deficits. This research-based review explores the therapeutic role of JAK-STAT, mTOR, and PPARγ signaling modulators in preventing neuronal dysfunctions in preclinical and clinical investigations.

R.ROSETTA: an interpretable machine learning framework

BACKGROUND

Machine learning involves strategies and algorithms that may assist bioinformatics analyses in terms of data mining and knowledge discovery. In several applications, viz. in Life Sciences, it is often more important to understand how a prediction was obtained rather than knowing what prediction was made. To this end so-called interpretable machine learning has been recently advocated. In this study, we implemented an interpretable machine learning package based on the rough set theory. An important aim of our work was provision of statistical properties of the models and their components.

RESULTS

We present the R.ROSETTA package, which is an R wrapper of ROSETTA framework. The original ROSETTA functions have been improved and adapted to the R programming environment. The package allows for building and analyzing non-linear interpretable machine learning models. R.ROSETTA gathers combinatorial statistics via rule-based modelling for accessible and transparent results, well-suited for adoption within the greater scientific community. The package also provides statistics and visualization tools that facilitate minimization of analysis bias and noise. The R.ROSETTA package is freely available at https://github.com/komorowskilab/R.ROSETTA . To illustrate the usage of the package, we applied it to a transcriptome dataset from an autism case-control study. Our tool provided hypotheses for potential co-predictive mechanisms among features that discerned phenotype classes. These co-predictors represented neurodevelopmental and autism-related genes.

CONCLUSIONS

R.ROSETTA provides new insights for interpretable machine learning analyses and knowledge-based systems. We demonstrated that our package facilitated detection of dependencies for autism-related genes. Although the sample application of R.ROSETTA illustrates transcriptome data analysis, the package can be used to analyze any data organized in decision tables.

Autism-related behaviors in the cyclooxygenase-2-deficient mouse model

Prostaglandin E2 (PGE2) is an endogenous lipid molecule involved in normal brain development. Cyclooxygenase-2 (COX2) is the main regulator of PGE2 synthesis. Emerging clinical and molecular research provides compelling evidence that abnormal COX2/PGE2 signaling is associated with autism spectrum disorder (ASD). We previously found that COX2 knockout mice had dysregulated expression of many ASD genes belonging to important biological pathways for neurodevelopment. The present study is the first to show the connection between irregular COX2/PGE2 signaling and autism-related behaviors in male and female COX2-deficient knockin, (COX)-2^- , mice at young (4-6 weeks) or adult (8-11 weeks) ages. Autism-related behaviors were prominent in male (COX)-2^- mice for most behavioral tests. In the open field test, (COX)-2^- mice traveled more than controls and adult male (COX)-2^- mice spent less time in the center indicating elevated hyperactive and anxiety-linked behaviors. (COX)-2^- mice also buried more marbles, with males burying more than females, suggesting increased anxiety and repetitive behaviors. Young male (COX)-2^- mice fell more frequently in the inverted screen test revealing motor deficits. The three-chamber sociability test found that adult female (COX)-2^- mice spent less time in the novel mouse chamber indicative of social abnormalities. In addition, male (COX)-2^- mice showed altered expression of several autism-linked genes: Wnt2, Glo1, Grm5 and Mmp9. Overall, our findings offer new insight into the involvement of disrupted COX2/PGE2 signaling in ASD pathology with age-related differences and greater impact on males. We propose that (COX)-2^- mice might serve as a novel model system to study specific types of autism.

Integrative computational evaluation of genetic markers for Alzheimer's disease

Recent studies have reported hundreds of genes linked to Alzheimer’s Disease (AD). However, many of these candidate genes may be not identified in different studies when analyses were replicated. Moreover, results could be controversial. Here, we proposed a computational workflow to curate and evaluate AD related genes. The method integrates large scale literature knowledge data and gene expression data that were acquired from postmortem human brain regions (AD case/control: 31/32 and 22/8). Pathway Enrichment, Sub-Network Enrichment, and Gene-Gene Interaction analysis were conducted to study the pathogenic profile of the candidate genes, with 4 metrics proposed and validated for each gene. By using our approach, a scalable AD genetic database was developed, including AD related genes, pathways, diseases and info of supporting references. The AD case/control classification supported the effectiveness of the 4 proposed metrics, which successfully identified 21 well-studied AD genes (i.g. TGFB1, CTNNB1, APP, IL1B, PSEN1, PTGS2, IL6, VEGFA, SOD1, AKT1, CDK5, TNF, GSK3B, TP53, CCL2, BDNF, NGF, IGF1, SIRT1, AGER and TLR) and highlighted one recently reported AD gene (i.g. ITGB1). The computational biology approach and the AD database developed in this study provide a valuable resource which may facilitate the understanding of the AD genetic profile.

Microarray analysis of gene expression in the cyclooxygenase knockout mice - a connection to autism spectrum disorder

The cellular and molecular events that take place during brain development play an important role in governing function of the mature brain. Lipid-signalling molecules such as prostaglandin E₂ (PGE₂ ) play an important role in healthy brain development. Abnormalities along the COX-PGE₂ signalling pathway due to genetic or environmental causes have been linked to autism spectrum disorder (ASD). This study aims to evaluate the effect of altered COX-PGE₂ signalling on development and function of the prenatal brain using male mice lacking cyclooxygenase-1 and cyclooxygenase-2 (COX-1^-/- and COX-2^-/- ) as potential model systems of ASD. Microarray analysis was used to determine global changes in gene expression during embryonic days 16 (E16) and 19 (E19). Gene Ontology: Biological Process (GO:BP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were implemented to identify affected developmental genes and cellular processes. We found that in both knockouts the brain at E16 had nearly twice as many differentially expressed genes, and affected biological pathways containing various ASD-associated genes important in neuronal function. Interestingly, using GeneMANIA and Cytoscape we also show that the ASD-risk genes identified in both COX-1^-/- and COX-2^-/- models belong to protein-interaction networks important for brain development despite of different cellular localization of these enzymes. Lastly, we identified eight genes that belong to the Wnt signalling pathways exclusively in the COX-2^-/- mice at E16. The level of PKA-phosphorylated β-catenin (S552), a major activator of the Wnt pathway, was increased in this model, suggesting crosstalk between the COX-2-PGE₂ and Wnt pathways during early brain development. Overall, these results provide further molecular insight into the contribution of the COX-PGE₂ pathways to ASD and demonstrate that COX-1^-/- and COX-2^-/- animals might be suitable new model systems for studying the disorders.

Neurodevelopmental Perspectives on Wnt Signaling in Psychiatry

Mounting evidence indicates that Wnt signaling is relevant to pathophysiology of diverse mental illnesses including schizophrenia, bipolar disorder, and autism spectrum disorder. In the 35 years since Wnt ligands were first described, animal studies have richly explored how downstream Wnt signaling pathways affect an array of neurodevelopmental processes and how their disruption can lead to both neurological and behavioral phenotypes. Recently, human induced pluripotent stem cell (hiPSC) models have begun to contribute to this literature while pushing it in increasingly translational directions. Simultaneously, large-scale human genomic studies are providing evidence that sequence variation in Wnt signal pathway genes contributes to pathogenesis in several psychiatric disorders. This article reviews neurodevelopmental and postneurodevelopmental functions of Wnt signaling, highlighting mechanisms, whereby its disruption might contribute to psychiatric illness, and then reviews the most reliable recent genetic evidence supporting that mutations in Wnt pathway genes contribute to psychiatric illness. We are proponents of the notion that studies in animal and hiPSC models informed by the human genetic data combined with the deep knowledge base and tool kits generated over the last several decades of basic neurodevelopmental research will yield near-term tangible advances in neuropsychiatry.

Food for thought: dietary changes in essential fatty acid ratios and the increase in autism spectrum disorders

The last decades have shown a spectacular and partially unexplained rise in the prevalence of autism spectrum disorders (ASD). This rise in ASD seems to parallel changes in the dietary composition of fatty acids. This change is marked by the replacement of cholesterol by omega-6 (n-6) fatty acids in many of our food products, resulting in a drastically increased ratio of omega-6/omega-3 (n-6/n-3). In this context, we review the available knowledge on the putative role of fatty acids in neurodevelopment and describe how disturbances in n-6/n-3 ratios may contribute to the emergence of ASDs. Both clinical and experimental research is discussed. We argue that a change in the ratio of n-6/n-3, especially during early life, may induce developmental changes in brain connectivity, synaptogenesis, cognition and behavior that are directly related to ASD.

Prostaglandin E2 alters Wnt-dependent migration and proliferation in neuroectodermal stem cells: implications for autism spectrum disorders

Prostaglandin E2 (PGE₂) is a natural lipid-derived molecule that is involved in important physiological functions. Abnormal PGE₂ signalling has been associated with pathologies of the nervous system. Previous studies provide evidence for the interaction of PGE₂ and canonical Wnt signalling pathways in non-neuronal cells. Since the Wnt pathway is crucial in the development and organization of the brain, the main goal of this study is to determine whether collaboration between these pathways exists in neuronal cell types. We report that PGE₂ interacts with canonical Wnt signalling through PKA and PI-3K in neuroectodermal (NE-4C) stem cells. We used time-lapse microscopy to determine that PGE₂ increases the final distance from origin, path length travelled, and the average speed of migration in Wnt-activated cells. Furthermore, PGE₂ alters distinct cellular phenotypes that are characteristic of Wnt-induced NE-4C cells, which corresponds to the modified splitting behaviour of the cells. We also found that in Wnt-induced cells the level of β-catenin protein was increased and the expression levels of Wnt-target genes (Ctnnb1, Ptgs2, Ccnd1, Mmp9) was significantly upregulated in response to PGE₂ treatment. This confirms that PGE₂ activated the canonical Wnt signalling pathway. Furthermore, the upregulated genes have been previously associated with ASD. Our findings show, for the first time, evidence for cross-talk between PGE₂ and Wnt signalling in neuronal cells, where PKA and PI-3K might act as mediators between the two pathways. Given the importance of PGE₂ and Wnt signalling in prenatal development of the nervous system, our study provides insight into how interaction between these two pathways may influence neurodevelopment.

Developing a Deeper Understanding of Autism: Connecting Knowledge through Literature Mining

In the field of autism, an enormous increase in available information makes it very difficult to connect fragments of knowledge into a more coherent picture. We present a literature mining method, RaJoLink, to search for matched themes in unrelated literature that may contribute to a better understanding of complex pathological conditions, such as autism. 214 full text articles on autism, published in PubMed, served as a source of data. Using ontology construction, we identified the main concepts of what is already known about autism. Then, the RaJoLink method, based on Swanson's ABC model, was used to reveal potentially interesting, but not yet investigated, connections between different concepts in research. Among the more interesting concepts identified with RaJoLink in our study were calcineurin and NF-kappaB. Both terms can be linked to neuro-immune abnormalities in the brain of patients with autism. Further research is needed to provide stronger evidence about calcineurin and NF-kappaB involvement in autism. However, the analysis presented confirms that this method could support experts on their way towards discovering hidden relationships and towards a better understanding of the disorder.

The neurobiology of lipid metabolism in autism spectrum disorders

Autism is a neurodevelopmental disorder characterized by impairments in communication and reciprocal social interaction, coupled with repetitive behavior, which typically manifests by 3 years of age. Multiple genes and early exposure to environmental factors are the etiological determinants of the disorder that contribute to variable expression of autism-related traits. Increasing evidence indicates that altered fatty acid metabolic pathways may affect proper function of the nervous system and contribute to autism spectrum disorders. This review provides an overview of the reported abnormalities associated with the synthesis of membrane fatty acids in individuals with autism as a result of insufficient dietary supplementation or genetic defects. Moreover, we discuss deficits associated with the release of arachidonic acid from the membrane phospholipids and its subsequent metabolism to bioactive prostaglandins via phospholipase A(2)-cyclooxygenase biosynthetic pathway in autism spectrum disorders. The existing evidence for the involvement of lipid neurobiology in the pathology of neurodevelopmental disorders such as autism is compelling and opens up an interesting possibility for further investigation of this metabolic pathway.

Association study between single nucleotide polymorphisms in promoter region of AVPR1A and Korean autism spectrum disorders

To determine the association between arginine vasopressin receptor 1A gene (AVPR1A) and autism spectrum disorders (ASDs), we examined 3 single nucleotide polymorphisms (SNPs), namely, rs7294536, rs3759292, and rs10877969, in the promoter region of AVPR1A by using a family-based association test (FBAT) in 151 Korean trios. Our results demonstrated a statistically significant association between autism and SNPs (additive model: rs7294536, chi(2)=9.328, df=2, P=0.002; rs10877969, chi(2)=11.529, df=2, P<0.001) as well as between autism and haplotype analysis (additive model: chi(2)=14.122, df=3, P=0.003). In addition, we found that ADI-R scores calculated by using a diagnostic algorithm for failure to develop peer relationships (A2) were higher in subjects having the AA genotype than in subjects having the AG and GG genotypes of rs7294536. Thus, our study provides evidence for a possible association between these SNPs and the phenotype of ASDs.