Transient peripheral blood transcriptomic response to ketamine treatment in children with ADNP syndrome.

Activity-dependent neuroprotective protein (ADNP) syndrome is a rare neurodevelopmental disorder resulting in intellectual disability, developmental delay and autism spectrum disorder (ASD) and is due to mutations in the ADNP gene. Ketamine treatment has emerged as a promising therapeutic option for ADNP syndrome, showing safety and apparent behavioral improvements in a first open label study. However, the molecular perturbations induced by ketamine remain poorly understood. Here, we investigated the longitudinal effect of ketamine on the blood transcriptome of 10 individuals with ADNP syndrome. Transcriptomic profiling was performed before and at multiple time points after a single low-dose intravenous ketamine infusion (0.5 mg/kg). We show that ketamine triggers immediate and profound gene expression alterations, with specific enrichment of monocyte-related expression patterns. These acute alterations encompass diverse signaling pathways and co-expression networks, implicating upregulation of immune and inflammatory-related processes and down-regulation of RNA processing mechanisms and metabolism. Notably, these changes exhibit a transient nature, returning to baseline levels 24 hours to 1 week after treatment. These findings enhance our understanding of ketamine's molecular effects and lay the groundwork for further research elucidating its specific cellular and molecular targets. Moreover, they contribute to the development of therapeutic strategies for ADNP syndrome and potentially, ASD more broadly.

Divergent landscapes of A-to-I editing in postmortem and living human brain.

Adenosine-to-inosine (A-to-I) editing is a prevalent post-transcriptional RNA modification within the brain. Yet, most research has relied on postmortem samples, assuming it is an accurate representation of RNA biology in the living brain. We challenge this assumption by comparing A-to-I editing between postmortem and living prefrontal cortical tissues. Major differences were found, with over 70,000 A-to-I sites showing higher editing levels in postmortem tissues. Increased A-to-I editing in postmortem tissues is linked to higher ADAR and ADARB1 expression, is more pronounced in non-neuronal cells, and indicative of postmortem activation of inflammation and hypoxia. Higher A-to-I editing in living tissues marks sites that are evolutionarily preserved, synaptic, developmentally timed, and disrupted in neurological conditions. Common genetic variants were also found to differentially affect A-to-I editing levels in living versus postmortem tissues. Collectively, these discoveries offer more nuanced and accurate insights into the regulatory mechanisms of RNA editing in the human brain.

Divergent landscapes of A-to-I editing in postmortem and living human brain.

Adenosine-to-inosine (A-to-I) editing is a prevalent post-transcriptional RNA modification within the brain. Yet, most research has relied on postmortem samples, assuming it is an accurate representation of RNA biology in the living brain. We challenge this assumption by comparing A-to-I editing between postmortem and living prefrontal cortical tissues. Major differences were found, with over 70,000 A-to-I sites showing higher editing levels in postmortem tissues. Increased A-to-I editing in postmortem tissues is linked to higher ADAR1 and ADARB1 expression, is more pronounced in non-neuronal cells, and indicative of postmortem activation of inflammation and hypoxia. Higher A-to-I editing in living tissues marks sites that are evolutionarily preserved, synaptic, developmentally timed, and disrupted in neurological conditions. Common genetic variants were also found to differentially affect A-to-I editing levels in living versus postmortem tissues. Collectively, these discoveries illuminate the nuanced functions and intricate regulatory mechanisms of RNA editing within the human brain.

Multiomic foundations of human prefrontal cortex tissue function.

The prefrontal cortex (PFC) is a region of the brain that in humans is involved in the production of higher-order functions such as cognition, emotion, perception, and behavior. Neurotransmission in the PFC produces higher-order functions by integrating information from other areas of the brain. At the foundation of neurotransmission, and by extension at the foundation of higher-order brain functions, are an untold number of coordinated molecular processes involving the DNA sequence variants in the genome, RNA transcripts in the transcriptome, and proteins in the proteome. These "multiomic" foundations are poorly understood in humans, perhaps in part because most modern studies that characterize the molecular state of the human PFC use tissue obtained when neurotransmission and higher-order brain functions have ceased (i.e., the postmortem state). Here, analyses are presented on data generated for the Living Brain Project (LBP) to investigate whether PFC tissue from individuals with intact higher-order brain function has characteristic multiomic foundations. Two complementary strategies were employed towards this end. The first strategy was to identify in PFC samples obtained from living study participants a signature of RNA transcript expression associated with neurotransmission measured intracranially at the time of PFC sampling, in some cases while participants performed a task engaging higher-order brain functions. The second strategy was to perform multiomic comparisons between PFC samples obtained from individuals with intact higher-order brain function at the time of sampling (i.e., living study participants) and PFC samples obtained in the postmortem state. RNA transcript expression within multiple PFC cell types was associated with fluctuations of dopaminergic, serotonergic, and/or noradrenergic neurotransmission in the substantia nigra measured while participants played a computer game that engaged higher-order brain functions. A subset of these associations - termed the "transcriptional program associated with neurotransmission" (TPAWN) - were reproduced in analyses of brain RNA transcript expression and intracranial neurotransmission data obtained from a second LBP cohort and from a cohort in an independent study. RNA transcripts involved in TPAWN were found to be (1) enriched for RNA transcripts associated with measures of neurotransmission in rodent and cell models, (2) enriched for RNA transcripts encoded by evolutionarily constrained genes, (3) depleted of RNA transcripts regulated by common DNA sequence variants, and (4) enriched for RNA transcripts implicated in higher-order brain functions by human population genetic studies. In PFC excitatory neurons of living study participants, higher expression of the genes in TPAWN tracked with higher expression of RNA transcripts that in rodent PFC samples are markers of a class of excitatory neurons that connect the PFC to deep brain structures. TPAWN was further reproduced by RNA transcript expression patterns differentiating living PFC samples from postmortem PFC samples, and significant differences between living and postmortem PFC samples were additionally observed with respect to (1) the expression of most primary RNA transcripts, mature RNA transcripts, and proteins, (2) the splicing of most primary RNA transcripts into mature RNA transcripts, (3) the patterns of co-expression between RNA transcripts and proteins, and (4) the effects of some DNA sequence variants on RNA transcript and protein expression. Taken together, this report highlights that studies of brain tissue obtained in a safe and ethical manner from large cohorts of living individuals can help advance understanding of the multiomic foundations of brain function.

Transient peripheral blood transcriptomic response to ketamine treatment in children with ADNP syndrome.

Activity-dependent neuroprotective protein (ADNP) syndrome is a rare neurodevelopmental disorder resulting in intellectual disability, developmental delay and autism spectrum disorder (ASD) and is due to mutations in the ADNP gene. Ketamine treatment has emerged as a promising therapeutic option for ADNP syndrome, showing safety and apparent behavioral improvements in a first open label study. However, the molecular perturbations induced by ketamine remain poorly understood. Here, we investigated the longitudinal effect of ketamine on the blood transcriptome of 10 individuals with ADNP syndrome. Transcriptomic profiling was performed before and at multiple time points after a single low-dose intravenous ketamine infusion (0.5mg/kg). We show that ketamine triggers immediate and profound gene expression alterations, with specific enrichment of monocyte-related expression patterns. These acute alterations encompass diverse signaling pathways and co-expression networks, implicating up-regulation of immune and inflammatory-related processes and down-regulation of RNA processing mechanisms and metabolism. Notably, these changes exhibit a transient nature, returning to baseline levels 24 hours to 1 week after treatment. These findings enhance our understanding of ketamine's molecular effects and lay the groundwork for further research elucidating its specific cellular and molecular targets. Moreover, they contribute to the development of therapeutic strategies for ADNP syndrome and potentially, ASD more broadly.

A primer on the use of machine learning to distil knowledge from data in biological psychiatry.

Applications of machine learning in the biomedical sciences are growing rapidly. This growth has been spurred by diverse cross-institutional and interdisciplinary collaborations, public availability of large datasets, an increase in the accessibility of analytic routines, and the availability of powerful computing resources. With this increased access and exposure to machine learning comes a responsibility for education and a deeper understanding of its bases and bounds, borne equally by data scientists seeking to ply their analytic wares in medical research and by biomedical scientists seeking to harness such methods to glean knowledge from data. This article provides an accessible and critical review of machine learning for a biomedically informed audience, as well as its applications in psychiatry. The review covers definitions and expositions of commonly used machine learning methods, and historical trends of their use in psychiatry. We also provide a set of standards, namely Guidelines for REporting Machine Learning Investigations in Neuropsychiatry (GREMLIN), for designing and reporting studies that use machine learning as a primary data-analysis approach. Lastly, we propose the establishment of the Machine Learning in Psychiatry (MLPsych) Consortium, enumerate its objectives, and identify areas of opportunity for future applications of machine learning in biological psychiatry. This review serves as a cautiously optimistic primer on machine learning for those on the precipice as they prepare to dive into the field, either as methodological practitioners or well-informed consumers.

Acetate supplementation rescues social deficits and alters transcriptional regulation in prefrontal cortex of Shank3 deficient mice.

BACKGROUND: The pathophysiology of autism spectrum disorder (ASD) involves genetic and environmental factors. Mounting evidence demonstrates a role for the gut microbiome in ASD, with signaling via short-chain fatty acids (SCFA) as one mechanism. Here, we utilize mice carrying deletion to exons 4-22 of Shank3 (Shank3KO) to model gene by microbiome interactions in ASD. We identify SCFA acetate as a mediator of gut-brain interactions and show acetate supplementation reverses social deficits concomitant with alterations to medial prefrontal cortex (mPFC) transcriptional regulation independent of microbiome status. METHODS: Shank3KO and wild-type (Wt) littermates were divided into control, Antibiotic (Abx), Acetate and Abx + Acetate groups upon weaning. After six weeks, animals underwent behavioral testing. Molecular analysis including 16S and metagenomic sequencing, metabolomic and transcriptional profiling were conducted. Additionally, targeted serum metabolomic data from Phelan McDermid Syndrome (PMS) patients (who are heterozygous for the Shank3 gene) were leveraged to assess levels of SCFA's relative to ASD clinical measures. RESULTS: Shank3KO mice were found to display social deficits, dysregulated gut microbiome and decreased cecal levels of acetate - effects exacerbated by Abx treatment. RNA-sequencing of mPFC showed unique gene expression signature induced by microbiome depletion in the Shank3KO mice. Oral treatment with acetate reverses social deficits and results in marked changes in gene expression enriched for synaptic signaling, pathways among others, even in Abx treated mice. Clinical data showed sex specific correlations between levels of acetate and hyperactivity scores. CONCLUSION: These results suggest a key role for the gut microbiome and the neuroactive metabolite acetate in regulating ASD-like behaviors.

Wearable and Non-Invasive Sensors for Rock Climbing Applications: Science-Based Training and Performance Optimization.

Rock climbing has evolved from a method for alpine mountaineering into a popular recreational activity and competitive sport. Advances in safety equipment and the rapid growth of indoor climbing facilities has enabled climbers to focus on the physical and technical movements needed to elevate performance. Through improved training methods, climbers can now achieve ascents of extreme difficulty. A critical aspect to further improve performance is the ability to continuously measure body movement and physiologic responses while ascending the climbing wall. However, traditional measurement devices (e.g., dynamometer) limit data collection during climbing. Advances in wearable and non-invasive sensor technologies have enabled new applications for climbing. This paper presents an overview and critical analysis of the scientific literature on sensors used during climbing. We focus on the several highlighted sensors with the ability to provide continuous measurements during climbing. These selected sensors consist of five main types (body movement, respiration, heart activity, eye gazing, skeletal muscle characterization) that demonstrate their capabilities and potential climbing applications. This review will facilitate the selection of these types of sensors in support of climbing training and strategies.

Microenvironment Tracker (MicroTrac) model to estimate time-location of individuals for air pollution exposure assessments: model evaluation using smartphone data.

BACKGROUND: A critical aspect of air pollution exposure assessments is determining the time spent in various microenvironments (ME), which can have substantially different pollutant concentrations. We previously developed and evaluated a ME classification model, called Microenvironment Tracker (MicroTrac), to estimate time of day and duration spent in eight MEs (indoors and outdoors at home, work, school; inside vehicles; other locations) based on input data from global positioning system (GPS) loggers. OBJECTIVE: In this study, we extended MicroTrac and evaluated the ability of using geolocation data from smartphones to determine the time spent in the MEs. METHOD: We performed a panel study, and the MicroTrac estimates based on data from smartphones and GPS loggers were compared to 37 days of diary data across five participants. RESULTS: The MEs were correctly classified for 98.1% and 98.3% of the time spent by the participants using smartphones and GPS loggers, respectively. SIGNIFICANCE: Our study demonstrates the extended capability of using ubiquitous smartphone data with MicroTrac to help reduce time-location uncertainty in air pollution exposure models for epidemiologic and exposure field studies.

Large 22q13.3 deletions perturb peripheral transcriptomic and metabolomic profiles in Phelan-McDermid syndrome.

Phelan-McDermid syndrome (PMS) is a rare neurodevelopmental disorder caused at least in part by haploinsufficiency of the SHANK3 gene, due to sequence variants in SHANK3 or subtelomeric 22q13.3 deletions. Phenotypic differences have been reported between PMS participants carrying small "class I" mutations and large "class II" mutations; however, the molecular perturbations underlying these divergent phenotypes remain obscure. Using peripheral blood transcriptome and serum metabolome profiling, we examined the molecular perturbations in the peripheral circulation associated with a full spectrum of PMS genotypes spanning class I (n = 37) and class II mutations (n = 39). Transcriptomic data revealed 52 genes with blood expression profiles that tightly scale with 22q.13.3 deletion size. Furthermore, we uncover 208 underexpressed genes in PMS participants with class II mutations, which were unchanged in class I mutations. These genes were not linked to 22q13.3 and were strongly enriched for glycosphingolipid metabolism, NCAM1 interactions, and cytotoxic natural killer (NK) immune cell signatures. In silico predictions estimated a reduction in CD56+ CD16- NK cell proportions in class II mutations, which was validated by mass cytometry time of flight. Global metabolomics profiling identified 24 metabolites that were significantly altered in PMS participants with class II mutations and confirmed a general reduction in sphingolipid metabolism. Collectively, these results provide new evidence linking PMS participants carrying class II mutations with decreased expression of cytotoxic cell signatures, reduced relative proportions of NK cells, and lower sphingolipid metabolism. These findings highlight alternative avenues for therapeutic development and offer new mechanistic insights supporting genotype-to-phenotype associations in PMS.

Spatiotemporal and genetic regulation of A-to-I editing throughout human brain development.

Posttranscriptional RNA modifications by adenosine-to-inosine (A-to-I) editing are abundant in the brain, yet elucidating functional sites remains challenging. To bridge this gap, we investigate spatiotemporal and genetically regulated A-to-I editing sites across prenatal and postnatal stages of human brain development. More than 10,000 spatiotemporally regulated A-to-I sites were identified that occur predominately in 3' UTRs and introns, as well as 37 sites that recode amino acids in protein coding regions with precise changes in editing levels across development. Hyper-edited transcripts are also enriched in the aging brain and stabilize RNA secondary structures. These features are conserved in murine and non-human primate models of neurodevelopment. Finally, thousands of cis-editing quantitative trait loci (edQTLs) were identified with unique regulatory effects during prenatal and postnatal development. Collectively, this work offers a resolved atlas linking spatiotemporal variation in editing levels to genetic regulatory effects throughout distinct stages of brain maturation.

Modeling gene × environment interactions in PTSD using human neurons reveals diagnosis-specific glucocorticoid-induced gene expression.

Post-traumatic stress disorder (PTSD) can develop following severe trauma, but the extent to which genetic and environmental risk factors contribute to individual clinical outcomes is unknown. Here, we compared transcriptional responses to hydrocortisone exposure in human induced pluripotent stem cell (hiPSC)-derived glutamatergic neurons and peripheral blood mononuclear cells (PBMCs) from combat veterans with PTSD (n = 19 hiPSC and n = 20 PBMC donors) and controls (n = 20 hiPSC and n = 20 PBMC donors). In neurons only, we observed diagnosis-specific glucocorticoid-induced changes in gene expression corresponding with PTSD-specific transcriptomic patterns found in human postmortem brains. We observed glucocorticoid hypersensitivity in PTSD neurons, and identified genes that contribute to this PTSD-dependent glucocorticoid response. We find evidence of a coregulated network of transcription factors that mediates glucocorticoid hyper-responsivity in PTSD. These findings suggest that induced neurons represent a platform for examining the molecular mechanisms underlying PTSD, identifying biomarkers of stress response, and conducting drug screening to identify new therapeutics.

Integrating Wearable Sensors and Video to Determine Microlocation-Specific Physiologic and Motion Biometrics-Method Development for Competitive Climbing.

Competitive indoor climbing has increased in popularity at the youth, collegiate, and Olympic levels. A critical aspect for improving performance is characterizing the physiologic response to different climbing strategies (e.g., work/rest patterns, pacing) and techniques (e.g., body position and movement) relative to location on climbing wall with spatially varying characteristics (e.g., wall inclinations, position of foot/hand holds). However, this response is not well understood due to the limited capabilities of climbing-specific measurement and assessment tools. In this study, we developed a novel method to examine time-resolved sensor-based measurements of multiple personal biometrics at different microlocations (finely spaced positions; MLs) along a climbing route. For the ML-specific biometric system (MLBS), we integrated continuous data from wearable biometric sensors and smartphone-based video during climbing, with a customized visualization and analysis system to determine three physiologic parameters (heart rate, breathing rate, ventilation rate) and one body movement parameter (hip acceleration), which are automatically time-matched to the corresponding video frame to determine ML-specific biometrics. Key features include: (1) biometric sensors that are seamlessly embedded in the fabric of an athletic compression shirt, and do not interfere with climbing performance, (2) climbing video, and (3) an interactive graphical user interface to rapidly visualize and analyze the time-matched biometrics and climbing video, determine timing sequence between the biometrics at key events, and calculate summary statistics. To demonstrate the capabilities of MLBS, we examined the relationship between changes in ML-specific climbing characteristics and changes in the physiologic parameters. Our study demonstrates the ability of MLBS to determine multiple time-resolved biometrics at different MLs, in support of developing and assessing different climbing strategies and training methods to help improve performance.

Cellular and genetic drivers of RNA editing variation in the human brain.

Posttranscriptional adenosine-to-inosine modifications amplify the functionality of RNA molecules in the brain, yet the cellular and genetic regulation of RNA editing is poorly described. We quantify base-specific RNA editing across three major cell populations from the human prefrontal cortex: glutamatergic neurons, medial ganglionic eminence-derived GABAergic neurons, and oligodendrocytes. We identify more selective editing and hyper-editing in neurons relative to oligodendrocytes. RNA editing patterns are highly cell type-specific, with 189,229 cell type-associated sites. The cellular specificity for thousands of sites is confirmed by single nucleus RNA-sequencing. Importantly, cell type-associated sites are enriched in GTEx RNA-sequencing data, edited ~twentyfold higher than all other sites, and variation in RNA editing is largely explained by neuronal proportions in bulk brain tissue. Finally, we uncover 661,791 cis-editing quantitative trait loci across thirteen brain regions, including hundreds with cell type-associated features. These data reveal an expansive repertoire of highly regulated RNA editing sites across human brain cell types and provide a resolved atlas linking cell types to editing variation and genetic regulatory effects.

Integrating human brain proteomes with genome-wide association data implicates novel proteins in post-traumatic stress disorder.

Genome-wide association studies (GWAS) have identified several risk loci for post-traumatic stress disorder (PTSD); however, how they confer PTSD risk remains unclear. We aimed to identify genes that confer PTSD risk through their effects on brain protein abundance to provide new insights into PTSD pathogenesis. To that end, we integrated human brain proteomes with PTSD GWAS results to perform a proteome-wide association study (PWAS) of PTSD, followed by Mendelian randomization, using a discovery and confirmatory study design. Brain proteomes (N = 525) were profiled from the dorsolateral prefrontal cortex using mass spectrometry. The Million Veteran Program (MVP) PTSD GWAS (n = 186,689) was used for the discovery PWAS, and the Psychiatric Genomics Consortium PTSD GWAS (n = 174,659) was used for the confirmatory PWAS. To understand whether genes identified at the protein-level were also evident at the transcript-level, we performed a transcriptome-wide association study (TWAS) using human brain transcriptomes (N = 888) and the MVP PTSD GWAS results. We identified 11 genes that contribute to PTSD pathogenesis via their respective cis-regulated brain protein abundance. Seven of 11 genes (64%) replicated in the confirmatory PWAS and 4 of 11 also had their cis-regulated brain mRNA levels associated with PTSD. High confidence level was assigned to 9 of 11 genes after considering evidence from the confirmatory PWAS and TWAS. Most of the identified genes are expressed in other PTSD-relevant brain regions and several are preferentially expressed in excitatory neurons, astrocytes, and oligodendrocyte precursor cells. These genes are novel, promising targets for mechanistic and therapeutic studies to find new treatments for PTSD.

Brain microRNAs are associated with variation in cognitive trajectory in advanced age.

In advancing age, some individuals maintain a stable cognitive performance over time, while others experience a rapid decline. Such variation in cognitive trajectory is only partially explained by common neurodegenerative pathologies. Hence, we aimed to identify new molecular processes underlying variation in cognitive trajectory using brain microRNA profile followed by an integrative analysis with brain transcriptome and proteome. Individual cognitive trajectories were derived from longitudinally assessed cognitive-test scores of older-adult brain donors from four longitudinal cohorts. Postmortem brain microRNA profiles, transcriptomes, and proteomes were derived from the dorsolateral prefrontal cortex. The global microRNA association study of cognitive trajectory was performed in a discovery (n = 454) and replication cohort (n = 134), followed by a meta-analysis that identified 6 microRNAs. Among these, miR-132-3p and miR-29a-3p were most significantly associated with cognitive trajectory. They explain 18.2% and 2.0% of the variance of cognitive trajectory, respectively, and act independently of the eight measured neurodegenerative pathologies. Furthermore, integrative transcriptomic and proteomic analyses revealed that miR-132-3p was significantly associated with 24 of the 47 modules of co-expressed genes of the transcriptome, miR-29a-3p with 3 modules, and identified 84 and 214 downstream targets of miR-132-3p and miR-29a-3p, respectively, in cognitive trajectory. This is the first global microRNA study of cognitive trajectory to our knowledge. We identified miR-29a-3p and miR-132-3p as novel and robust contributors to cognitive trajectory independently of the eight known cerebral pathologies. Our findings lay a foundation for future studies investigating mechanisms and developing interventions to enhance cognitive stability in advanced age.

Cell-Type-Specific Impact of Glucocorticoid Receptor Activation on the Developing Brain: A Cerebral Organoid Study.

OBJECTIVE: A fine-tuned balance of glucocorticoid receptor (GR) activation is essential for organ formation, with disturbances influencing many health outcomes. In utero, glucocorticoids have been linked to brain-related negative outcomes, with unclear underlying mechanisms, especially regarding cell-type-specific effects. An in vitro model of fetal human brain development, induced human pluripotent stem cell (hiPSC)-derived cerebral organoids, was used to test whether cerebral organoids are suitable for studying the impact of prenatal glucocorticoid exposure on the developing brain. METHODS: The GR was activated with the synthetic glucocorticoid dexamethasone, and the effects were mapped using single-cell transcriptomics across development. RESULTS: The GR was expressed in all cell types, with increasing expression levels through development. Not only did its activation elicit translocation to the nucleus and the expected effects on known GR-regulated pathways, but also neurons and progenitor cells showed targeted regulation of differentiation- and maturation-related transcripts. Uniquely in neurons, differentially expressed transcripts were significantly enriched for genes associated with behavior-related phenotypes and disorders. This human neuronal glucocorticoid response profile was validated across organoids from three independent hiPSC lines reprogrammed from different source tissues from both male and female donors. CONCLUSIONS: These findings suggest that excessive glucocorticoid exposure could interfere with neuronal maturation in utero, leading to increased disease susceptibility through neurodevelopmental processes at the interface of genetic susceptibility and environmental exposure. Cerebral organoids are a valuable translational resource for exploring the effects of glucocorticoids on early human brain development.

Integrating Personal Air Sensor and GPS to Determine Microenvironment-Specific Exposures to Volatile Organic Compounds.

Personal exposure to volatile organic compounds (VOCs) from indoor sources including consumer products is an understudied public health concern. To develop and evaluate methods for monitoring personal VOC exposures, we performed a pilot study and examined time-resolved sensor-based measurements of geocoded total VOC (TVOC) exposures across individuals and microenvironments (MEs). We integrated continuous (1 min) data from a personal TVOC sensor and a global positioning system (GPS) logger, with a GPS-based ME classification model, to determine TVOC exposures in four MEs, including indoors at home (Home-In), indoors at other buildings (Other-In), inside vehicles (In-Vehicle), and outdoors (Out), across 45 participant-days for five participants. To help identify places with large emission sources, we identified high-exposure events (HEEs; TVOC > 500 ppb) using geocoded TVOC time-course data overlaid on Google Earth maps. Across the 45 participant-days, the MEs ranked from highest to lowest median TVOC were: Home-In (165 ppb), Other-In (86 ppb), In-Vehicle (52 ppb), and Out (46 ppb). For the two participants living in single-family houses with attached garages, the median exposures for Home-In were substantially higher (209, 416 ppb) than the three participant homes without attached garages: one living in a single-family house (129 ppb), and two living in apartments (38, 60 ppb). The daily average Home-In exposures exceeded the estimated Leadership in Energy and Environmental Design (LEED) building guideline of 108 ppb for 60% of the participant-days. We identified 94 HEEs across all participant-days, and 67% of the corresponding peak levels exceeded 1000 ppb. The MEs ranked from the highest to the lowest number of HEEs were: Home-In (60), Other-In (13), In-Vehicle (12), and Out (9). For Other-In and Out, most HEEs occurred indoors at fast food restaurants and retail stores, and outdoors in parking lots, respectively. For Home-In HEEs, the median TVOC emission and removal rates were 5.4 g h-1 and 1.1 h-1, respectively. Our study demonstrates the ability to determine individual sensor-based time-resolved TVOC exposures in different MEs, in support of identifying potential sources and exposure factors that can inform exposure mitigation strategies.

Prospective and detailed behavioral phenotyping in DDX3X syndrome.

BACKGROUND: DDX3X syndrome is a recently identified genetic disorder that accounts for 1-3% of cases of unexplained developmental delay and/or intellectual disability (ID) in females, and is associated with motor and language delays, and autism spectrum disorder (ASD). To date, the published phenotypic characterization of this syndrome has primarily relied on medical record review; in addition, the behavioral dimensions of the syndrome have not been fully explored. METHODS: We carried out multi-day, prospective, detailed phenotyping of DDX3X syndrome in 14 females and 1 male, focusing on behavioral, psychological, and neurological measures. Three participants in this cohort were previously reported with limited phenotype information and were re-evaluated for this study. We compared results against population norms and contrasted phenotypes between individuals harboring either (1) protein-truncating variants or (2) missense variants or in-frame deletions. RESULTS: Eighty percent (80%) of individuals met criteria for ID, 60% for ASD and 53% for attention-deficit/hyperactivity disorder (ADHD). Motor and language delays were common as were sensory processing abnormalities. The cohort included 5 missense, 3 intronic/splice-site, 2 nonsense, 2 frameshift, 2 in-frame deletions, and one initiation codon variant. Genotype-phenotype correlations indicated that, on average, missense variants/in-frame deletions were associated with more severe language, motor, and adaptive deficits in comparison to protein-truncating variants. LIMITATIONS: Sample size is modest, however, DDX3X syndrome is a rare and underdiagnosed disorder. CONCLUSION: This study, representing a first, prospective, detailed characterization of DDX3X syndrome, extends our understanding of the neurobehavioral phenotype. Gold-standard diagnostic approaches demonstrated high rates of ID, ASD, and ADHD. In addition, sensory deficits were observed to be a key part of the syndrome. Even with a modest sample, we observe evidence for genotype-phenotype correlations with missense variants/in-frame deletions generally associated with more severe phenotypes.