Assessment of anxiety in children with neurodevelopment disorders: Rasch analysis of the Spence Children's Anxiety Scale.

Anxiety is common in neurodevelopmental disorders (NDD). The parent version of the Spence Children's Anxiety Scale (SCAS-P) is a widely used measure to assess anxiety across a broad range of childhood populations. However, assessment of the measurement properties of the SCAS-P in NDDs have been limited. The present study aimed to assess the psychometric properties of the SCAS-P in children with attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) using Rasch Measurement Theory. Data from the Province of Ontario Neurodevelopmental Disorders Network Registry were used in the analysis. Children (ages 6-13 years old) with a primary diagnosis of ADHD (n=146) or ASD (n=104) were administered the SCAS-P. Rasch Measurement Theory was used to assess measurement properties of the SCAS-P, including unidimensionality and item-level fit, category ordering, item targeting, person separation index and reliability and differential item functioning. The SCAS-P fit well to the Rasch model in both ADHD and ASD, including unidimensionality, satisfactory category ordering and goodness-of-fit. However, item-person measures showed poor precision at lower levels of anxiety. Some items showed differential item functioning, including items within the obsessive-compulsive, panic/agoraphobia and physical injury fears domains, suggesting that the presentation of anxiety may differ between ADHD and ASD. Overall, the results generally support the use of the SCAS-P to screen and monitor anxiety symptoms in children with ADHD and ASD. Future studies would benefit from examination of more severely anxious NDD cohort, including those with clinically diagnosed anxiety.

Rasch analyses of the Quick Inventory of Depressive Symptomatology Self-Report in neurodegenerative and major depressive disorders.

Background: Symptoms of depression are present in neurodegenerative disorders (ND). It is important that depression-related symptoms be adequately screened and monitored in persons living with ND. The Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR) is a widely-used self-report measure to assess and monitor depressive severity across different patient populations. However, the measurement properties of the QIDS-SR have not been assessed in ND. Aim: To use Rasch Measurement Theory to assess the measurement properties of the Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR) in ND and in comparison to major depressive disorder (MDD). Methods: De-identified data from the Ontario Neurodegenerative Disease Research Initiative (NCT04104373) and Canadian Biomarker Integration Network in Depression (NCT01655706) were used in the analyses. Five hundred and twenty participants with ND (Alzheimer's disease or mild cognitive impairment, amyotrophic lateral sclerosis, cerebrovascular disease, frontotemporal dementia and Parkinson's disease) and 117 participants with major depressive disorder (MDD) were administered the QIDS-SR. Rasch Measurement Theory was used to assess measurement properties of the QIDS-SR, including unidimensionality and item-level fit, category ordering, item targeting, person separation index and reliability and differential item functioning. Results: The QIDS-SR fit well to the Rasch model in ND and MDD, including unidimensionality, satisfactory category ordering and goodness-of-fit. Item-person measures (Wright maps) showed gaps in item difficulties, suggesting poor precision for persons falling between those severity levels. Differences between mean person and item measures in the ND cohort logits suggest that QIDS-SR items target more severe depression than experienced by the ND cohort. Some items showed differential item functioning between cohorts. Conclusion: The present study supports the use of the QIDS-SR in MDD and suggest that the QIDS-SR can be also used to screen for depressive symptoms in persons with ND. However, gaps in item targeting were noted that suggests that the QIDS-SR cannot differentiate participants falling within certain severity levels. Future studies would benefit from examination in a more severely depressed ND cohort, including those with diagnosed clinical depression.

FAIR in action: Brain-CODE - A neuroscience data sharing platform to accelerate brain research.

The effective sharing of health research data within the healthcare ecosystem can have tremendous impact on the advancement of disease understanding, prevention, treatment, and monitoring. By combining and reusing health research data, increasingly rich insights can be made about patients and populations that feed back into the health system resulting in more effective best practices and better patient outcomes. To achieve the promise of a learning health system, data needs to meet the FAIR principles of findability, accessibility, interoperability, and reusability. Since the inception of the Brain-CODE platform and services in 2012, the Ontario Brain Institute (OBI) has pioneered data sharing activities aligned with FAIR principles in neuroscience. Here, we describe how Brain-CODE has operationalized data sharing according to the FAIR principles. Findable-Brain-CODE offers an interactive and itemized approach for requesters to generate data cuts of interest that align with their research questions. Accessible-Brain-CODE offers multiple data access mechanisms. These mechanisms-that distinguish between metadata access, data access within a secure computing environment on Brain-CODE and data access via export will be discussed. Interoperable-Standardization happens at the data capture level and the data release stage to allow integration with similar data elements. Reusable - Brain-CODE implements several quality assurances measures and controls to maximize data value for reusability. We will highlight the successes and challenges of a FAIR-focused neuroinformatics platform that facilitates the widespread collection and sharing of neuroscience research data for learning health systems.

Common Data Elements to Facilitate Sharing and Re-use of Participant-Level Data: Assessment of Psychiatric Comorbidity Across Brain Disorders.

The Ontario Brain Institute's "Brain-CODE" is a large-scale informatics platform designed to support the collection, storage and integration of diverse types of data across several brain disorders as a means to understand underlying causes of brain dysfunction and developing novel approaches to treatment. By providing access to aggregated datasets on participants with and without different brain disorders, Brain-CODE will facilitate analyses both within and across diseases and cover multiple brain disorders and a wide array of data, including clinical, neuroimaging, and molecular. To help achieve these goals, consensus methodology was used to identify a set of core demographic and clinical variables that should be routinely collected across all participating programs. Establishment of Common Data Elements within Brain-CODE is critical to enable a high degree of consistency in data collection across studies and thus optimize the ability of investigators to analyze pooled participant-level data within and across brain disorders. Results are also presented using selected common data elements pooled across three studies to better understand psychiatric comorbidity in neurological disease (Alzheimer's disease/amnesic mild cognitive impairment, amyotrophic lateral sclerosis, cerebrovascular disease, frontotemporal dementia, and Parkinson's disease).

Plasma microRNA expression levels and their targeted pathways in patients with major depressive disorder who are responsive to duloxetine treatment.

Major depressive disorder (MDD) is a complex disorder with many pathways known to contribute to its pathogenesis, such as apoptotic signaling, with antidepressants having been shown to target these pathways. In this study, we explored microRNAs as predictive markers of drug response to duloxetine, a serotonin-norepinephrine reuptake inhibiter, using peripheral blood samples from 3 independent clinical trials (NCT00635219; NCT0059991; NCT01140906) comparing 6-8 weeks of treatment with duloxetine to placebo treatment in patients with MDD. Plasma microRNA was extracted and sequenced using the Ion Proton Sequencer. Rank feature selection analysis was used to identify microRNAs in the top 10th percentile for their differentiating ability between patients who remitted and did not remit with duloxetine treatment. The results were then compared between the 3 trials to see their replicability. To further validate our findings, we reasoned that the pathways targeted by these microRNAs would be those shown to be altered in MDD in pathway enrichment analysis. Hsa-miR-23a-3p, hsa-miR-16-5p, hsa-miR-146a-5p and hsa-miR-21-5p were identified in 2 or more trials as being able to differentiate patients who would remit with duloxetine treatment using samples collected before treatment initiation, suggesting that they may be good candidates for identification of predictive biomarkers of duloxetine response. Pathway enrichment analysis further showed that microRNAs identified as differentiating for duloxetine response target the apoptosis signaling pathway. Future studies examining these microRNAs outside of a clinical trial setting and exploring their role in MDD may further our understanding of MDD and antidepressant response.

The CAMH Neuroinformatics Platform: A Hospital-Focused Brain-CODE Implementation.

Investigations of mental illness have been enriched by the advent and maturation of neuroimaging technologies and the rapid pace and increased affordability of molecular sequencing techniques, however, the increased volume, variety and velocity of research data, presents a considerable technical and analytic challenge to curate, federate and interpret. Aggregation of high-dimensional datasets across brain disorders can increase sample sizes and may help identify underlying causes of brain dysfunction, however, additional barriers exist for effective data harmonization and integration for their combined use in research. To help realize the potential of multi-modal data integration for the study of mental illness, the Centre for Addiction and Mental Health (CAMH) constructed a centralized data capture, visualization and analytics environment-the CAMH Neuroinformatics Platform-based on the Ontario Brain Institute (OBI) Brain-CODE architecture, towards the curation of a standardized, consolidated psychiatric hospital-wide research dataset, directly coupled to high performance computing resources.

Brain-CODE: A Secure Neuroinformatics Platform for Management, Federation, Sharing and Analysis of Multi-Dimensional Neuroscience Data.

Historically, research databases have existed in isolation with no practical avenue for sharing or pooling medical data into high dimensional datasets that can be efficiently compared across databases. To address this challenge, the Ontario Brain Institute's "Brain-CODE" is a large-scale neuroinformatics platform designed to support the collection, storage, federation, sharing and analysis of different data types across several brain disorders, as a means to understand common underlying causes of brain dysfunction and develop novel approaches to treatment. By providing researchers access to aggregated datasets that they otherwise could not obtain independently, Brain-CODE incentivizes data sharing and collaboration and facilitates analyses both within and across disorders and across a wide array of data types, including clinical, neuroimaging and molecular. The Brain-CODE system architecture provides the technical capabilities to support (1) consolidated data management to securely capture, monitor and curate data, (2) privacy and security best-practices, and (3) interoperable and extensible systems that support harmonization, integration, and query across diverse data modalities and linkages to external data sources. Brain-CODE currently supports collaborative research networks focused on various brain conditions, including neurodevelopmental disorders, cerebral palsy, neurodegenerative diseases, epilepsy and mood disorders. These programs are generating large volumes of data that are integrated within Brain-CODE to support scientific inquiry and analytics across multiple brain disorders and modalities. By providing access to very large datasets on patients with different brain disorders and enabling linkages to provincial, national and international databases, Brain-CODE will help to generate new hypotheses about the biological bases of brain disorders, and ultimately promote new discoveries to improve patient care.

Enu mutagenesis identifies a novel platelet phenotype in a loss-of-function Jak2 allele.

Utilizing ENU mutagenesis, we identified a mutant mouse with elevated platelets. Genetic mapping localized the mutation to an interval on chromosome 19 that encodes the Jak2 tyrosine kinase. We identified a A3056T mutation resulting in a premature stop codon within exon 19 of Jak2 (Jak2(K915X)), resulting in a protein truncation and functionally inactive enzyme. This novel platelet phenotype was also observed in mice bearing a hemizygous targeted disruption of the Jak2 locus (Jak2(+/-)). Timed pregnancy experiments revealed that Jak2(K915X/K915X) and Jak2(-/-) displayed embryonic lethality; however, Jak2(K915X/K915X) embryos were viable an additional two days compared to Jak2(-/-) embryos. Our data suggest that perturbing JAK2 activation may have unexpected consequences in elevation of platelet number and correspondingly, important implications for treatment of hematological disorders with constitutive Jak2 activity.

CBL linker region and RING finger mutations lead to enhanced granulocyte-macrophage colony-stimulating factor (GM-CSF) signaling via elevated levels of JAK2 and LYN.

Juvenile myelomonocytic leukemia (JMML) is characterized by hypersensitivity to granulocyte-macrophage colony-stimulating factor (GM-CSF). SHP2, NF-1, KRAS, and NRAS are mutated in JMML patients, leading to aberrant regulation of RAS signaling. A subset of JMML patients harbor CBL mutations associated with 11q acquired uniparental disomy. Many of these mutations are in the linker region and the RING finger of CBL, leading to a loss of E3 ligase activity. We investigated the mechanism by which CBL-Y371H, a linker region mutant, and CBL-C384R, a RING finger mutant, lead to enhanced GM-CSF signaling. Expression of CBL mutants in the TF-1 cell line resulted in enhanced survival in the absence of GM-CSF. Cells expressing CBL mutations displayed increased phosphorylation of GM-CSF receptor ßc subunit in response to stimulation, although expression of total GM-CSFR ßc was lower. This suggested enhanced kinase activity downstream of GM-CSFR. JAK2 and LYN kinase expression is elevated in CBL-Y371H and CBL-C384R mutant cells, resulting in enhanced phosphorylation of CBL and S6 in response to GM-CSF stimulation. Incubation with the JAK2 inhibitor, TG101348, abolished the increased phosphorylation of GM-CSFR ßc in cells expressing CBL mutants, whereas treatment with the SRC kinase inhibitor dasatinib resulted in equalization of GM-CSFR ßc phosphorylation signal between wild type CBL and CBL mutant samples. Dasatinib treatment inhibited the elevated phosphorylation of CBL-Y371H and CBL-C384R mutants. Our study indicates that CBL linker and RING finger mutants lead to enhanced GM-CSF signaling due to elevated kinase expression, which can be blocked using small molecule inhibitors targeting specific downstream pathways.

The SH2B1 adaptor protein associates with a proximal region of the erythropoietin receptor.

Gene targeting experiments have shown that the cytokine erythropoietin (EPO), its cognate erythropoietin receptor (EPO-R), and associated Janus tyrosine kinase, JAK2, are all essential for erythropoiesis. Structural-functional and murine knock-in experiments have suggested that EPO-R Tyr-343 is important in EPO-mediated mitogenesis. Although Stat5 binds to EPO-R phosphotyrosine 343, the initial Stat5-deficient mice did not have profound erythroid abnormalities suggesting that additional Src homology 2 (SH2) domain-containing effectors may bind to EPO-R Tyr-343 and couple to downstream signaling pathways. We have utilized cloning of ligand target (COLT) screening to demonstrate that EPO-R Tyr(P)-343 and Tyr(P)-401 bind to the SH2 domain-containing adaptor protein SH2B1ß. Immunoprecipitation and in vitro mixing experiments reveal that EPO-R binds to SH2B1 in an SH2 domain-dependent manner and that the sequence that confers SH2B1 binding to the EPO-R is pYXXL. Previous studies have shown that SH2B1 binds directly to JAK2, but we show that in hematopoietic cells, SH2B1ß preferentially associates with the EPO-R. SH2B1 is capable of constitutive association with EPO-R, which is necessary for its optimal SH2-dependent recruitment to EPO-R-Tyr(P)-343/Tyr(P)-401. We also demonstrate that SH2B1 is responsive to EPO stimulation and becomes phosphorylated, most likely on serines/threonines, in an EPO dose- and time-dependent manner. In the absence of SH2B1, we observe enhanced activation of signaling pathways downstream of the EPO-R, indicating that SH2B1 is a negative regulator of EPO signaling.

Targeted deletion of fgl2 leads to impaired regulatory T cell activity and development of autoimmune glomerulonephritis.

Mice with targeted deletion of fibrinogen-like protein 2 (fgl2) spontaneously developed autoimmune glomerulonephritis with increasing age, as did wild-type recipients reconstituted with fgl2-/- bone marrow. These data implicate FGL2 as an important immunoregulatory molecule and led us to identify the underlying mechanisms. Deficiency of FGL2, produced by CD4+CD25+ regulatory T cells (Treg), resulted in increased T cell proliferation to lectins and alloantigens, Th 1 polarization, and increased numbers of Ab-producing B cells following immunization with T-independent Ags. Dendritic cells were more abundant in fgl2-/- mice and had increased expression of CD80 and MHCII following LPS stimulation. Treg cells were also more abundant in fgl2-/- mice, but their suppressive activity was significantly impaired. Ab to FGL2 completely inhibited Treg cell activity in vitro. FGL2 inhibited dendritic cell maturation and induced apoptosis of B cells through binding to the low-affinity FcgammaRIIB receptor. Collectively, these data suggest that FGL2 contributes to Treg cell activity and inhibits the development of autoimmune disease.

Targeted deletion of Fgl-2/fibroleukin in the donor modulates immunologic response and acute vascular rejection in cardiac xenografts.

BACKGROUND: Xenografts ultimately fail as a result of acute vascular rejection (AVR), a process characterized by intravascular thrombosis, fibrin deposition, and endothelial cell activation. METHODS AND RESULTS: We studied whether targeted deletion of Fgl-2, an inducible endothelial cell procoagulant, (Fgl-2-/-) in the donor prevents AVR in a mouse-to-rat cardiac xenotransplantation model. By 3 days after transplant, Fgl-2+/+ grafts developed typical features of AVR associated with increased levels of donor Fgl-2 mRNA. Grafts from Fgl-2-/- mice had reduced fibrin deposition but developed cellular rejection. Treatment with a short course of cobra venom factor and maintenance cyclosporine resulted in long-term acceptance of both Fgl-2+/+ and Fgl-2-/- grafts. On withdrawal of cyclosporine, Fgl-2+/+ grafts developed features of AVR; in contrast, Fgl-2-/- grafts again developed acute cellular rejection. Rejecting Fgl-2+/+ hearts stained positively for IgG, IgM, C3, and C5b-9, whereas rejecting Fgl-2-/- hearts had minimal Ig and complement deposition despite xenoantibodies in the serum. Furthermore, serum containing xenoantibodies failed to stain Fgl-2-/- long-term treated hearts but did stain wild-type heart tissues. Treatment of Fgl-2-/- xenografts with mycophenolate mofetil and tacrolimus, a clinically relevant immune suppression protocol, led to long-term graft acceptance. CONCLUSIONS: Deletion of Fgl-2 ameliorates AVR by downregulation of xenoantigens and may facilitate successful clinical heart xenotransplantation.