PSMD11 loss-of-function variants correlate with a neurobehavioral phenotype, obesity, and increased interferon response.

Primary proteasomopathies have recently emerged as a new class of rare early-onset neurodevelopmental disorders (NDDs) caused by pathogenic variants in the PSMB1, PSMC1, PSMC3, or PSMD12 proteasome genes. Proteasomes are large multi-subunit protein complexes that maintain cellular protein homeostasis by clearing ubiquitin-tagged damaged, misfolded, or unnecessary proteins. In this study, we have identified PSMD11 as an additional proteasome gene in which pathogenic variation is associated with an NDD-causing proteasomopathy. PSMD11 loss-of-function variants caused early-onset syndromic intellectual disability and neurodevelopmental delay with recurrent obesity in 10 unrelated children. Our findings demonstrate that the cognitive impairment observed in these individuals could be recapitulated in Drosophila melanogaster with depletion of the PMSD11 ortholog Rpn6, which compromised reversal learning. Our investigations in subject samples further revealed that PSMD11 loss of function resulted in impaired 26S proteasome assembly and the acquisition of a persistent type I interferon (IFN) gene signature, mediated by the integrated stress response (ISR) protein kinase R (PKR). In summary, these data identify PSMD11 as an additional member of the growing family of genes associated with neurodevelopmental proteasomopathies and provide insights into proteasomal biology in human health.

Developing a Chatbot to Support Individuals With Neurodevelopmental Disorders: Tutorial.

Families of individuals with neurodevelopmental disabilities or differences (NDDs) often struggle to find reliable health information on the web. NDDs encompass various conditions affecting up to 14% of children in high-income countries, and most individuals present with complex phenotypes and related conditions. It is challenging for their families to develop literacy solely by searching information on the internet. While in-person coaching can enhance care, it is only available to a minority of those with NDDs. Chatbots, or computer programs that simulate conversation, have emerged in the commercial sector as useful tools for answering questions, but their use in health care remains limited. To address this challenge, the researchers developed a chatbot named CAMI (Coaching Assistant for Medical/Health Information) that can provide information about trusted resources covering core knowledge and services relevant to families of individuals with NDDs. The chatbot was developed, in collaboration with individuals with lived experience, to provide information about trusted resources covering core knowledge and services that may be of interest. The developers used the Django framework (Django Software Foundation) for the development and used a knowledge graph to depict the key entities in NDDs and their relationships to allow the chatbot to suggest web resources that may be related to the user queries. To identify NDD domain-specific entities from user input, a combination of standard sources (the Unified Medical Language System) and other entities were used which were identified by health professionals as well as collaborators. Although most entities were identified in the text, some were not captured in the system and therefore went undetected. Nonetheless, the chatbot was able to provide resources addressing most user queries related to NDDs. The researchers found that enriching the vocabulary with synonyms and lay language terms for specific subdomains enhanced entity detection. By using a data set of numerous individuals with NDDs, the researchers developed a knowledge graph that established meaningful connections between entities, allowing the chatbot to present related symptoms, diagnoses, and resources. To the researchers' knowledge, CAMI is the first chatbot to provide resources related to NDDs. Our work highlighted the importance of engaging end users to supplement standard generic ontologies to named entities for language recognition. It also demonstrates that complex medical and health-related information can be integrated using knowledge graphs and leveraging existing large datasets. This has multiple implications: generalizability to other health domains as well as reducing the need for experts and optimizing their input while keeping health care professionals in the loop. The researchers' work also shows how health and computer science domains need to collaborate to achieve the granularity needed to make chatbots truly useful and impactful.

Bi-allelic HPDL Variants Cause a Neurodegenerative Disease Ranging from Neonatal Encephalopathy to Adolescent-Onset Spastic Paraplegia.

We report bi-allelic pathogenic HPDL variants as a cause of a progressive, pediatric-onset spastic movement disorder with variable clinical presentation. The single-exon gene HPDL encodes a protein of unknown function with sequence similarity to 4-hydroxyphenylpyruvate dioxygenase. Exome sequencing studies in 13 families revealed bi-allelic HPDL variants in each of the 17 individuals affected with this clinically heterogeneous autosomal-recessive neurological disorder. HPDL levels were significantly reduced in fibroblast cell lines derived from more severely affected individuals, indicating the identified HPDL variants resulted in the loss of HPDL protein. Clinical presentation ranged from severe, neonatal-onset neurodevelopmental delay with neuroimaging findings resembling mitochondrial encephalopathy to milder manifestation of adolescent-onset, isolated hereditary spastic paraplegia. All affected individuals developed spasticity predominantly of the lower limbs over the course of the disease. We demonstrated through bioinformatic and cellular studies that HPDL has a mitochondrial localization signal and consequently localizes to mitochondria suggesting a putative role in mitochondrial metabolism. Taken together, these genetic, bioinformatic, and functional studies demonstrate HPDL is a mitochondrial protein, the loss of which causes a clinically variable form of pediatric-onset spastic movement disorder.

Leveraging Knowledge Graphs and Natural Language Processing for Automated Web Resource Labeling and Knowledge Mobilization in Neurodevelopmental Disorders: Development and Usability Study.

BACKGROUND: Patients and families need to be provided with trusted information more than ever with the abundance of online information. Several organizations aim to build databases that can be searched based on the needs of target groups. One such group is individuals with neurodevelopmental disorders (NDDs) and their families. NDDs affect up to 18% of the population and have major social and economic impacts. The current limitations in communicating information for individuals with NDDs include the absence of shared terminology and the lack of efficient labeling processes for web resources. Because of these limitations, health professionals, support groups, and families are unable to share, combine, and access resources. OBJECTIVE: We aimed to develop a natural language-based pipeline to label resources by leveraging standard and free-text vocabularies obtained through text analysis, and then represent those resources as a weighted knowledge graph. METHODS: Using a combination of experts and service/organization databases, we created a data set of web resources for NDDs. Text from these websites was scraped and collected into a corpus of textual data on NDDs. This corpus was used to construct a knowledge graph suitable for use by both experts and nonexperts. Named entity recognition, topic modeling, document classification, and location detection were used to extract knowledge from the corpus. RESULTS: We developed a resource annotation pipeline using diverse natural language processing algorithms to annotate web resources and stored them in a structured knowledge graph. The graph contained 78,181 annotations obtained from the combination of standard terminologies and a free-text vocabulary obtained using topic modeling. An application of the constructed knowledge graph is a resource search interface using the ordered weighted averaging operator to rank resources based on a user query. CONCLUSIONS: We developed an automated labeling pipeline for web resources on NDDs. This work showcases how artificial intelligence-based methods, such as natural language processing and knowledge graphs for information representation, can enhance knowledge extraction and mobilization, and could be used in other fields of medicine.

Deciphering the Diversity of Mental Models in Neurodevelopmental Disorders: Knowledge Graph Representation of Public Data Using Natural Language Processing.

BACKGROUND: Understanding how individuals think about a topic, known as the mental model, can significantly improve communication, especially in the medical domain where emotions and implications are high. Neurodevelopmental disorders (NDDs) represent a group of diagnoses, affecting up to 18% of the global population, involving differences in the development of cognitive or social functions. In this study, we focus on 2 NDDs, attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), which involve multiple symptoms and interventions requiring interactions between 2 important stakeholders: parents and health professionals. There is a gap in our understanding of differences between mental models for each stakeholder, making communication between stakeholders more difficult than it could be. OBJECTIVE: We aim to build knowledge graphs (KGs) from web-based information relevant to each stakeholder as proxies of mental models. These KGs will accelerate the identification of shared and divergent concerns between stakeholders. The developed KGs can help improve knowledge mobilization, communication, and care for individuals with ADHD and ASD. METHODS: We created 2 data sets by collecting the posts from web-based forums and PubMed abstracts related to ADHD and ASD. We utilized the Unified Medical Language System (UMLS) to detect biomedical concepts and applied Positive Pointwise Mutual Information followed by truncated Singular Value Decomposition to obtain corpus-based concept embeddings for each data set. Each data set is represented as a KG using a property graph model. Semantic relatedness between concepts is calculated to rank the relation strength of concepts and stored in the KG as relation weights. UMLS disorder-relevant semantic types are used to provide additional categorical information about each concept's domain. RESULTS: The developed KGs contain concepts from both data sets, with node sizes representing the co-occurrence frequency of concepts and edge sizes representing relevance between concepts. ADHD- and ASD-related concepts from different semantic types shows diverse areas of concerns and complex needs of the conditions. KG identifies converging and diverging concepts between health professionals literature (PubMed) and parental concerns (web-based forums), which may correspond to the differences between mental models for each stakeholder. CONCLUSIONS: We show for the first time that generating KGs from web-based data can capture the complex needs of families dealing with ADHD or ASD. Moreover, we showed points of convergence between families and health professionals' KGs. Natural language processing-based KG provides access to a large sample size, which is often a limiting factor for traditional in-person mental model mapping. Our work offers a high throughput access to mental model maps, which could be used for further in-person validation, knowledge mobilization projects, and basis for communication about potential blind spots from stakeholders in interactions about NDDs. Future research will be needed to identify how concepts could interact together differently for each stakeholder.

Leukoencephalopathy with calcifications and cysts: Genetic and phenotypic spectrum.

Biallelic mutations in SNORD118, encoding the small nucleolar RNA U8, cause leukoencephalopathy with calcifications and cysts (LCC). Given the difficulty in interpreting the functional consequences of variants in nonprotein encoding genes, and the high allelic polymorphism across SNORD118 in controls, we set out to provide a description of the molecular pathology and clinical spectrum observed in a cohort of patients with LCC. We identified 64 affected individuals from 56 families. Age at presentation varied from 3 weeks to 67 years, with disease onset after age 40 years in eight patients. Ten patients had died. We recorded 44 distinct, likely pathogenic, variants in SNORD118. Fifty two of 56 probands were compound heterozygotes, with parental consanguinity reported in only three families. Forty nine of 56 probands were either heterozygous (46) or homozygous (three) for a mutation involving one of seven nucleotides that facilitate a novel intramolecular interaction between the 5' end and 3' extension of precursor-U8. There was no obvious genotype-phenotype correlation to explain the marked variability in age at onset. Complementing recently published functional analyses in a zebrafish model, these data suggest that LCC most often occurs due to combinatorial severe and milder mutations, with the latter mostly affecting 3' end processing of precursor-U8.

Mutations in CAPN1 Cause Autosomal-Recessive Hereditary Spastic Paraplegia.

Hereditary spastic paraplegia (HSP) is a genetically and clinically heterogeneous disease characterized by spasticity and weakness of the lower limbs with or without additional neurological symptoms. Although more than 70 genes and genetic loci have been implicated in HSP, many families remain genetically undiagnosed, suggesting that other genetic causes of HSP are still to be identified. HSP can be inherited in an autosomal-dominant, autosomal-recessive, or X-linked manner. In the current study, we performed whole-exome sequencing to analyze a total of nine affected individuals in three families with autosomal-recessive HSP. Rare homozygous and compound-heterozygous nonsense, missense, frameshift, and splice-site mutations in CAPN1 were identified in all affected individuals, and sequencing in additional family members confirmed the segregation of these mutations with the disease (spastic paraplegia 76 [SPG76]). CAPN1 encodes calpain 1, a protease that is widely present in the CNS. Calpain 1 is involved in synaptic plasticity, synaptic restructuring, and axon maturation and maintenance. Three models of calpain 1 deficiency were further studied. In Caenorhabditis elegans, loss of calpain 1 function resulted in neuronal and axonal dysfunction and degeneration. Similarly, loss-of-function of the Drosophila melanogaster ortholog calpain B caused locomotor defects and axonal anomalies. Knockdown of calpain 1a, a CAPN1 ortholog in Danio rerio, resulted in abnormal branchiomotor neuron migration and disorganized acetylated-tubulin axonal networks in the brain. The identification of mutations in CAPN1 in HSP expands our understanding of the disease causes and potential mechanisms.

Conserved pharmacological rescue of hereditary spastic paraplegia-related phenotypes across model organisms.

Hereditary spastic paraplegias (HSPs) are a group of neurodegenerative diseases causing progressive gait dysfunction. Over 50 genes have now been associated with HSP. Despite the recent explosion in genetic knowledge, HSP remains without pharmacological treatment. Loss-of-function mutation of the SPAST gene, also known as SPG4, is the most common cause of HSP in patients. SPAST is conserved across animal species and regulates microtubule dynamics. Recent studies have shown that it also modulates endoplasmic reticulum (ER) stress. Here, utilizing null SPAST homologues in C. elegans, Drosophila and zebrafish, we tested FDA-approved compounds known to modulate ER stress in order to ameliorate locomotor phenotypes associated with HSP. We found that locomotor defects found in all of our spastin models could be partially rescued by phenazine, methylene blue, N-acetyl-cysteine, guanabenz and salubrinal. In addition, we show that established biomarkers of ER stress levels correlated with improved locomotor activity upon treatment across model organisms. Our results provide insights into biomarkers and novel therapeutic avenues for HSP.

G-Quadruplexes influence pri-microRNA processing.

RNA G-Quadruplexes (G4) have been shown to possess many biological functions, including the regulation of microRNA (miRNA) biogenesis and function. However, their impact on pri-miRNA processing remains unknown. We identified G4 located near the Drosha cleavage site in three distinct pri-miRNAs: pri-mir200c, pri-mir451a, and pri-mir497. The folding of the potential G4 motifs was determined in solution. Subsequently, mutations disrupting G4 folding led to important changes in the mature miRNAs levels in cells. Moreover, using small antisense oligonucleotides binding to the pri-miRNA, it was possible to modulate, either positively or negatively, the mature miRNA levels. Together, these data demonstrate that G4 motifs could contribute to the regulation of pri-mRNA processing, a novel role for G4. Considering that bio-informatics screening indicates that between 9% and 50% of all pri-miRNAs contain a putative G4, these structures possess interesting potential as future therapeutic targets.

Irregular G-quadruplexes Found in the Untranslated Regions of Human mRNAs Influence Translation.

G-quadruplex structures are composed of coplanar guanines and are found in both DNA and RNA. They are formed by the stacking of two or more G-quartets that are linked together by three loops. The current belief is that RNA G-quadruplexes include loops of l to 7 nucleotides in length, although recent evidence indicates that the central loop (loop 2) can be longer if loops 1 and 3 are limited to a single nucleotide each. With the objective of broadening the definition of irregular RNA G-quadruplexes, a bioinformatic search was performed to find potential G-quadruplexes located in the untranslated regions of human mRNAs (i.e. in the 5' and 3'-UTRs) that contain either a long loop 1 or 3 of up to 40 nucleotides in length. RNA molecules including the potential sequences were then synthesized and examined in vitro by in-line probing for the formation of G-quadruplex structures. The sequences that adopted a G-quadruplex structure were cloned into a luciferase dual vector and examined for their ability to modulate translation in cellulo Some irregular G-quadruplexes were observed to either promote or repress translation regardless of the position or the size of the long loop they possessed. Even if the composition of a RNA G-quadruplex is not quite completely understood, the results presented in this report clearly demonstrate that what defines a RNA G-quadruplex is much broader than what we previously believed.

Quantitative phenotypic and network analysis of 1q44 microdeletion for microcephaly.

As genome wide techniques become more common, an increasing proportion of patients with intellectual disability (ID) are found to have genetic defects allowing genotype-phenotype correlations. Previously, AKT3 deletion was suggested to be responsible for microcephaly in patients with 1q43-q44 deletion syndrome, but this does not correspond to all cases. We report a case of a de novo 1q44 deletion in an 8-year-old boy with microcephaly in whom AKT3 is not deleted. We used a systematic review of the literature, our patient, and network analysis to gain a better understanding of the genetic basis of microcephaly in 1q deletion patients. Our analysis showed that while AKT3 deletion is associated with more severe (≤3 SD) microcephaly in 1q43-q44 deletion patients, other genes may contribute to microcephaly in AKT3 intact patients with microcephaly and 1q43-44 deletion syndrome. We identified a potential role for HNRNPU, SMYD3, NLRP3, and KIF26B in microcephaly. Overall, our study highlights the need for network analysis and quantitative measures reporting in the phenotypic analysis of a complex genetic syndrome related to copy number variation.

PDE-4 inhibition rescues aberrant synaptic plasticity in Drosophila and mouse models of fragile X syndrome.

Fragile X syndrome (FXS) is the leading cause of both intellectual disability and autism resulting from a single gene mutation. Previously, we characterized cognitive impairments and brain structural defects in a Drosophila model of FXS and demonstrated that these impairments were rescued by treatment with metabotropic glutamate receptor (mGluR) antagonists or lithium. A well-documented biochemical defect observed in fly and mouse FXS models and FXS patients is low cAMP levels. cAMP levels can be regulated by mGluR signaling. Herein, we demonstrate PDE-4 inhibition as a therapeutic strategy to ameliorate memory impairments and brain structural defects in the Drosophila model of fragile X. Furthermore, we examine the effects of PDE-4 inhibition by pharmacologic treatment in the fragile X mouse model. We demonstrate that acute inhibition of PDE-4 by pharmacologic treatment in hippocampal slices rescues the enhanced mGluR-dependent LTD phenotype observed in FXS mice. Additionally, we find that chronic treatment of FXS model mice, in adulthood, also restores the level of mGluR-dependent LTD to that observed in wild-type animals. Translating the findings of successful pharmacologic intervention from the Drosophila model into the mouse model of FXS is an important advance, in that this identifies and validates PDE-4 inhibition as potential therapeutic intervention for the treatment of individuals afflicted with FXS.

Analyzing the Quality of Life in Individuals with Fragile X Syndrome in Relation to Sleep and Mental Health.

The purpose of this paper was to examine the physical, emotional, social and school functioning domains of quality of life of individuals with Fragile X Syndrome, in relation to mental health and sleep patterns to gain a better understanding of how these aspects are affected by the disorder. This study included 119 individuals with Fragile X Syndrome who were given different cognitive examinations by a neuropsychologist or by parent-proxy questionnaires. This study focused on the Pediatric Quality of Life Inventory (PedsQoL), the Anxiety, Depression and Mood Scale (ADAMS), the Children's Sleep Habits Questionnaire (CSHQ), but did include other cognitive tests (Vineland Adaptive Behaviour Scales, Nonverbal IQ, Autism Diagnostic Observation Schedule). We identified significant associations between decreases in emotional, social and school domains of PedsQoL and the ADAMS subtests of Generalized Anxiety, Manic/Hyperactivity and Obsessive/Compulsivity, with the subtest of Depressed Mood having associations with lower physical and emotional domains. We also identified a significant impact between CSHQ subtests of Sleep Anxiety, Night Wakings, Daytime Sleepiness, and Parasomnia with the emotional and school domains of PedsQoL. There were associations connecting school functioning with Bedtime Resistance, and additional associations connecting emotional functioning with Sleep Duration and Sleep Onset Delay. Physical functioning was also associated with Sleep Anxiety. Our study shows how mental health and sleep defects impact improper sleep patterns and mental health which leads to decreases in the quality of life for individuals with FXS, and how it is important to screen for these symptoms in order to alleviate issues.

Longitudinal follow-up of metformin treatment in Fragile X Syndrome.

Introduction: Metformin has been used as a targeted treatment to potentially improve cognition and slow the typical IQ decline that occurs during development among individuals with fragile X syndrome (FXS). In this follow-up study, we are following the trajectory of IQ and adaptive behavior changes over 1 to 3 years in individuals with FXS who are clinically treated with metformin in an open label trial. Method: Individuals with FXS ages 6 to 25 years (mean 13.15 ± 5.50) and nonverbal IQ mean 57.69 (±15.46) were treated for 1-3 years (1.88 ± 0.63). They all had a baseline IQ test using the Leiter-III non-verbal cognitive assessment and the Vineland-III adaptive behavior assessment before the start of metformin. Repeat Leiter-III and Vineland-III were completed after at least 1 year of metformin (500-1,000 mg/dose given twice a day). Result: There were no significant changes in non-verbal IQ or in the adaptive behavior measurements at FDR < 0.05. The findings thus far indicate that both IQ and adaptive behavior are stable over time, and we did not see a significant decline in either measure. Conclusion: Overall, the small sample size and short follow-up duration limit the interpretation of the effects of metformin on cognitive development and adaptive functioning. There is individual variability but overall for the group there was no significant decline in IQ or adaptive behavior.

Development of a highly optimized procedure for the discovery of RNA G-quadruplexes by combining several strategies.

RNA G-quadruplexes (rG4s) are non-canonical secondary structures that are formed by the self-association of guanine quartets and that are stabilized by monovalent cations (e.g. potassium). rG4s are key elements in several post-transcriptional regulation mechanisms, including both messenger RNA (mRNA) and microRNA processing, mRNA transport and translation, to name but a few examples. Over the past few years, multiple high-throughput approaches have been developed in order to identify rG4s, including bioinformatic prediction, in vitro assays and affinity capture experiments coupled to RNA sequencing. Each individual approach had its limits, and thus yielded only a fraction of the potential rG4 that are further confirmed (i.e., there is a significant level of false positive). This report aims to benefit from the strengths of several existing approaches to identify rG4s with a high potential of being folded in cells. Briefly, rG4s were pulled-down from cell lysates using the biotinylated biomimetic G4 ligand BioTASQ and the sequences thus isolated were then identified by RNA sequencing. Then, a novel bioinformatic pipeline that included DESeq2 to identify rG4 enriched transcripts, MACS2 to identify rG4 peaks, rG4-seq to increase rG4 formation probability and G4RNA Screener to detect putative rG4s was performed. This workflow uncovers new rG4 candidates whose rG4-folding was then confirmed in vitro using an array of established biophysical methods. Clearly, this workflow led to the identification of novel rG4s in a highly specific and reliable manner.

Long-term Memory Testing in Children With Typical Development and Neurodevelopmental Disorders: Remote Web-based Image Task Feasibility Study.

BACKGROUND: Neurodevelopmental disorders (NDD) cause individuals to have difficulty in learning facts, procedures, or social skills. NDD has been linked to several genes, and several animal models have been used to identify potential therapeutic candidates based on specific learning paradigms for long-term and associative memory. In individuals with NDD, however, such testing has not been used so far, resulting in a gap in translating preclinical results to clinical practice. OBJECTIVE: We aim to assess if individuals with NDD could be tested for paired association learning and long-term memory deficit, as shown in previous animal models. METHODS: We developed an image-based paired association task, which can be performed at different time points using remote web-based testing, and evaluated its feasibility in children with typical development (TD), as well as NDD. We included 2 tasks: object recognition as a simpler task and paired association. Learning was tested immediately after training and also the next day for long-term memory. RESULTS: We found that children aged 5-14 years with TD (n=128) and with NDD of different types (n=57) could complete testing using the Memory Game. Children with NDD showed deficits in both recognition and paired association tasks on the first day of learning, in both 5-9-year old (P<.001 and P=.01, respectively) and 10-14-year old groups (P=.001 and P<.001, respectively). The reaction times to stimuli showed no significant difference between individuals with TD or NDD. Children with NDD exhibited a faster 24-hour memory decay for the recognition task than those with TD in the 5-9-year old group. This trend is reversed for the paired association task. Interestingly, we found that children with NDD had their retention for recognition improved and matched with typically developing individuals by 10-14 years of age. The NDD group also showed improved retention deficits in the paired association task at 10-14 years of age compared to the TD group. CONCLUSIONS: We showed that web-based learning testing using simple picture association is feasible for children with TD, as well as with NDD. We showed how web-based testing allows us to train children to learn the association between pictures, as shown in immediate test results and those completed 1 day after. This is important as many models for learning deficits in NDD target both short- and long-term memory for therapeutic intervention. We also demonstrated that despite potential confounding factors, such as self-reported diagnosis bias, technical issues, and varied participation, the Memory Game shows significant differences between typically developing children and those with NDD. Future experiments will leverage this potential of web-based testing for larger cohorts and cross-validation with other clinical or preclinical cognitive tasks.

Fear of Reprisal and Change Agency in the Public Health and Social Service System: Protocol for a Sequential Mixed Methods Study.

BACKGROUND:  Since they are key witnesses to the systemic difficulties and social inequities experienced by vulnerable patients, health and social service (HSS) professionals and clinical managers must act as change agents. Using their expertise to achieve greater social justice, change agents employ a wide range of actions that span a continuum from the clinical (microsystem) to the societal (macrosystem) sphere and involve actors inside and outside the HSS system. Typically, however, clinical professionals and managers act in a circumscribed manner, that is, within the clinical sphere and with patients and colleagues. Among the hypotheses explaining this reduced scope of action is the fear of reprisal. Little is known about the prevalence of this fear and its complex dynamics. OBJECTIVE:  The overall aim is to gain a better understanding of the complex dynamic process leading to clinical professionals' and managers' fear of reprisal in their change agent actions and senior administrators' and managers' determination of wrongdoing. The objectives are (1) to estimate the prevalence of fear of reprisal among clinical professionals and managers; (2) to identify the factors involved in (a) the emergence of this fear among clinical professionals and managers, and (b) the determination of wrongdoing by senior administrators and managers; (3) to describe the process of emergence of (a) the fear of reprisal among clinical professionals and managers, and (b) the determination of wrongdoing by senior administrators and managers; and (4) to document the legal and ethical issues associated with the factors identified (objective 2) and the processes described (objective 3). METHODS:  Based on the Exit, Voice, Loyalty, Neglect model, a 3-part sequential mixed methods design will include (1) a web-based survey (objective 1), (2) a qualitative grounded theory design (objectives 2 and 3), and (3) legal and ethical analysis (objective 4). Survey: 77,794 clinical professionals or clinical managers working in the Québec public HSS system will be contacted via email. Data will be analyzed using descriptive statistics. Grounded theory design: for each of the 3 types of participants (clinical professionals, clinical managers, and senior administrators and managers), a theoretical sample of 15 to 30 people will be selected via various strategies. Data will be independently analyzed using constant comparison process. Legal and ethical analysis: situations described by participants will be analyzed using, respectively, applicable legislation and jurisprudence and 2 ethical models. RESULTS:  This ongoing study began in June 2022 and is scheduled for completion by March 2027. CONCLUSIONS:  Instead of acting, fear of reprisal could induce clinical professionals to tolerate situations that run counter to their social justice values. To ensure they use their capacities for serving a population that is or could become vulnerable, it is important to know the prevalence of the fear of reprisal and gain a better understanding of its complex dynamics. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/48400.

Sex difference contributes to phenotypic diversity in individuals with neurodevelopmental disorders.

Objective: Gain a better understanding of sex-specific differences in individuals with global developmental delay (GDD), with a focus on phenotypes and genotypes. Methods: Using the Deciphering Developmental Disorders (DDD) dataset, we extracted phenotypic information from 6,588 individuals with GDD and then identified statistically significant variations in phenotypes and genotypes based on sex. We compared genes with pathogenic variants between sex and then performed gene network and molecular function enrichment analysis and gene expression profiling between sex. Finally, we contrasted individuals with autism as an associated condition. Results: We identified significantly differentially expressed phenotypes in males vs. females individuals with GDD. Autism and macrocephaly were significantly more common in males whereas microcephaly and stereotypies were more common in females. Importantly, 66% of GDD genes with pathogenic variants overlapped between both sexes. In the cohort, males presented with only slightly increased X-linked genes (9% vs. 8%, respectively). Individuals from both sexes harbored a similar number of pathogenic variants overall (3) but females presented with a significantly higher load for GDD genes with high intolerance to loss of function. Sex difference in gene expression correlated with genes identified in a sex specific manner. While we identified sex-specific GDD gene mutations, their pathways overlapped. Interestingly, individuals with GDD but also co-morbid autism phenotypes, we observed distinct mutation load, pathways and phenotypic presentation. Conclusion: Our study shows for the first time that males and females with GDD present with significantly different phenotypes. Moreover, while most GDD genes overlapped, some genes were found uniquely in each sex. Surprisingly they shared similar molecular functions. Sorting genes by predicted tolerance to loss of function (pLI) led to identifying an increased mutation load in females with GDD, suggesting potentially a tolerance to GDD genes of higher pLI compared to overall GDD genes. Finally, we show that considering associated conditions (for instance autism) may influence the genomic underpinning found in individuals with GDD and highlight the importance of comprehensive phenotyping.

Developing a cluster-based approach for deciphering complexity in individuals with neurodevelopmental differences.

Objective: Individuals with neurodevelopmental disorders such as global developmental delay (GDD) present both genotypic and phenotypic heterogeneity. This diversity has hampered developing of targeted interventions given the relative rarity of each individual genetic etiology. Novel approaches to clinical trials where distinct, but related diseases can be treated by a common drug, known as basket trials, which have shown benefits in oncology but have yet to be used in GDD. Nonetheless, it remains unclear how individuals with GDD could be clustered. Here, we assess two different approaches: agglomerative and divisive clustering. Methods: Using the largest cohort of individuals with GDD, which is the Deciphering Developmental Disorders (DDD), characterized using a systematic approach, we extracted genotypic and phenotypic information from 6,588 individuals with GDD. We then used a k-means clustering (divisive) and hierarchical agglomerative clustering (HAC) to identify subgroups of individuals. Next, we extracted gene network and molecular function information with regard to the clusters identified by each approach. Results: HAC based on phenotypes identified in individuals with GDD revealed 16 clusters, each presenting with one dominant phenotype displayed by most individuals in the cluster, along with other minor phenotypes. Among the most common phenotypes reported were delayed speech, absent speech, and seizure. Interestingly, each phenotypic cluster molecularly included several (3-12) gene sub-networks of more closely related genes with diverse molecular function. k-means clustering also segregated individuals harboring those phenotypes, but the genetic pathways identified were different from the ones identified from HAC. Conclusion: Our study illustrates how divisive (k-means) and agglomerative clustering can be used in order to group individuals with GDD for future basket trials. Moreover, the result of our analysis suggests that phenotypic clusters should be subdivided into molecular sub-networks for an increased likelihood of successful treatment. Finally, a combination of both agglomerative and divisive clustering may be required for developing of a comprehensive treatment.