Enabling endpoint development for interventional clinical trials in individuals with Angelman syndrome: a prospective, longitudinal, observational clinical study (FREESIAS).

BACKGROUND: Angelman syndrome (AS) is a rare neurodevelopmental disorder characterized by the absence of a functional UBE3A gene, which causes developmental, behavioral, and medical challenges. While currently untreatable, comprehensive data could help identify appropriate endpoints assessing meaningful improvements in clinical trials. Herein are reported the results from the FREESIAS study assessing the feasibility and utility of in-clinic and at-home measures of key AS symptoms. METHODS: Fifty-five individuals with AS (aged < 5 years: n = 16, 5-12 years: n = 27, ≥ 18 years: n = 12; deletion genotype: n = 40, nondeletion genotype: n = 15) and 20 typically developing children (aged 1-12 years) were enrolled across six USA sites. Several clinical outcome assessments and digital health technologies were tested, together with overnight 19-lead electroencephalography (EEG) and additional polysomnography (PSG) sensors. Participants were assessed at baseline (Clinic Visit 1), 12 months later (Clinic Visit 2), and during intermittent home visits. RESULTS: The participants achieved high completion rates for the clinical outcome assessments (adherence: 89-100% [Clinic Visit 1]; 76-91% [Clinic Visit 2]) and varied feasibility of and adherence to digital health technologies. The coronavirus disease 2019 (COVID-19) pandemic impacted participants' uptake of and/or adherence to some measures. It also potentially impacted the at-home PSG/EEG recordings, which were otherwise feasible. Participants achieved Bayley-III results comparable to the available natural history data, showing similar scores between individuals aged ≥ 18 and 5-12 years. Also, participants without a deletion generally scored higher on most clinical outcome assessments than participants with a deletion. Furthermore, the observed AS EEG phenotype of excess delta-band power was consistent with prior reports. CONCLUSIONS: Although feasible clinical outcome assessments and digital health technologies are reported herein, further improved assessments of meaningful AS change are needed. Despite the COVID-19 pandemic, remote assessments facilitated high adherence levels and the results suggested that at-home PSG/EEG might be a feasible alternative to the in-clinic EEG assessments. Taken altogether, the combination of in-clinic/at-home clinical outcome assessments, digital health technologies, and PSG/EEG may improve protocol adherence, reduce patient burden, and optimize study outcomes in AS and other rare disease populations.

A natural history study to track brain and spinal cord changes in individuals with Friedreich's ataxia: TRACK-FA study protocol.

INTRODUCTION: Drug development for neurodegenerative diseases such as Friedreich's ataxia (FRDA) is limited by a lack of validated, sensitive biomarkers of pharmacodynamic response in affected tissue and disease progression. Studies employing neuroimaging measures to track FRDA have thus far been limited by their small sample sizes and limited follow up. TRACK-FA, a longitudinal, multi-site, and multi-modal neuroimaging natural history study, aims to address these shortcomings by enabling better understanding of underlying pathology and identifying sensitive, clinical trial ready, neuroimaging biomarkers for FRDA. METHODS: 200 individuals with FRDA and 104 control participants will be recruited across seven international study sites. Inclusion criteria for participants with genetically confirmed FRDA involves, age of disease onset ≤ 25 years, Friedreich's Ataxia Rating Scale (FARS) functional staging score of ≤ 5, and a total modified FARS (mFARS) score of ≤ 65 upon enrolment. The control cohort is matched to the FRDA cohort for age, sex, handedness, and years of education. Participants will be evaluated at three study visits over two years. Each visit comprises of a harmonized multimodal Magnetic Resonance Imaging (MRI) and Spectroscopy (MRS) scan of the brain and spinal cord; clinical, cognitive, mood and speech assessments and collection of a blood sample. Primary outcome measures, informed by previous neuroimaging studies, include measures of: spinal cord and brain morphometry, spinal cord and brain microstructure (measured using diffusion MRI), brain iron accumulation (using Quantitative Susceptibility Mapping) and spinal cord biochemistry (using MRS). Secondary and exploratory outcome measures include clinical, cognitive assessments and blood biomarkers. DISCUSSION: Prioritising immediate areas of need, TRACK-FA aims to deliver a set of sensitive, clinical trial-ready neuroimaging biomarkers to accelerate drug discovery efforts and better understand disease trajectory. Once validated, these potential pharmacodynamic biomarkers can be used to measure the efficacy of new therapeutics in forestalling disease progression. CLINICAL TRIAL REGISTRATION: ClinicalTrails.gov Identifier: NCT04349514.

Digital endpoints for self-administered home-based functional assessment in pediatric Friedreich's ataxia.

BACKGROUND: Friedreich's ataxia is an inherited, progressive, neurodegenerative disease that typically begins in childhood. Disease severity is commonly assessed with rating scales, such as the modified Friedreich's Ataxia Rating Scale, which are usually administered in the clinic by a neurology specialist. OBJECTIVE: This study evaluated the utility of home-based, self-administered digital endpoints in children with Friedreich's ataxia and unaffected controls and their relationship to standard clinical rating scales. METHODS: In a cross-sectional study with 25 participants (13 with Friedreich's ataxia and 12 unaffected controls, aged 6-15 years), home-based digital endpoints that reflect activities of daily living were recorded over 1 week. Domains analyzed were hand motor function with a digitized drawing, automated analysis of speech with a recorded oral diadochokinesis test, and gait and balance with wearable sensors. RESULTS: Hand-drawing and speech tests were easy to conduct and generated high-quality data. The sensor-based gait and balance tests suffered from technical limitations in this study setup. Several parameters discriminated between groups or correlated strongly with modified Friedreich's Ataxia Rating Scale total score and activities of daily living total score in the Friedreich's ataxia group. Hand-drawing parameters also strongly correlated with standard 9-hole peg test scores. INTERPRETATION: Deploying digital endpoints in home settings is feasible in this population, results in meaningful and robust data collection, and may allow for frequent sampling over longer periods of time to track disease progression. Care must be taken when training participants, and investigators should consider the complexity of the tasks and equipment used.

Measuring What Matters to Individuals with Angelman Syndrome and Their Families: Development of a Patient-Centered Disease Concept Model.

Angelman syndrome (AS) is a complex, heterogeneous, and life-long neurodevelopmental disorder. Despite the considerable impact on individuals and caregivers, no disease-modifying treatments are available. To support holistic clinical management and the development of AS-specific outcome measures for clinical studies, we conducted primary and secondary research identifying the impact of symptoms on individuals with AS and their unmet need. This qualitative research adopted a rigorous step-wise approach, aggregating information from published literature, then evaluating it via disease concept elicitation interviews with clinical experts and caregivers. We found that the AS-defining concepts most relevant for treatment included: impaired expressive communication, seizures, maladaptive behavior, cognitive impairment, motor function difficulties, sleep disturbance, and limited self-care abilities. We highlight the relevance of age in experiencing these key AS concepts, and the difference between the perceptions of clinicians and caregivers towards the syndrome. Finally, we outline the impact of AS on individuals, caregivers, and families.

Angelman syndrome genotypes manifest varying degrees of clinical severity and developmental impairment.

Angelman Syndrome (AS) is a severe neurodevelopmental disorder due to impaired expression of UBE3A in neurons. There are several genetic mechanisms that impair UBE3A expression, but they differ in how neighboring genes on chromosome 15 at 15q11-q13 are affected. There is evidence that different genetic subtypes present with different clinical severity, but a systematic quantitative investigation is lacking. Here we analyze natural history data on a large sample of individuals with AS (n = 250, 848 assessments), including clinical scales that quantify development of motor, cognitive, and language skills (Bayley Scales of Infant Development, Third Edition; Preschool Language Scale, Fourth Edition), adaptive behavior (Vineland Adaptive Behavioral Scales, Second Edition), and AS-specific symptoms (AS Clinical Severity Scale). We found that clinical severity, as captured by these scales, differs between genetic subtypes: individuals with UBE3A pathogenic variants and imprinting defects (IPD) are less affected than individuals with uniparental paternal disomy (UPD); of those with UBE3A pathogenic variants, individuals with truncating mutations are more impaired than those with missense mutations. Individuals with a deletion that encompasses UBE3A and other genes are most impaired, but in contrast to previous work, we found little evidence for an influence of deletion length (class I vs. II) on severity of manifestations. The results of this systematic analysis highlight the relevance of genomic regions beyond UBE3A as contributing factors in the AS phenotype, and provide important information for the development of new therapies for AS. More generally, this work exemplifies how increasing genetic irregularities are reflected in clinical severity.

Decreased microglial Wnt/ß-catenin signalling drives microglial pro-inflammatory activation in the developing brain.

Microglia of the developing brain have unique functional properties but how their activation states are regulated is poorly understood. Inflammatory activation of microglia in the still-developing brain of preterm-born infants is associated with permanent neurological sequelae in 9 million infants every year. Investigating the regulators of microglial activation in the developing brain across models of neuroinflammation-mediated injury (mouse, zebrafish) and primary human and mouse microglia we found using analysis of genes and proteins that a reduction in Wnt/ß-catenin signalling is necessary and sufficient to drive a microglial phenotype causing hypomyelination. We validated in a cohort of preterm-born infants that genomic variation in the Wnt pathway is associated with the levels of connectivity found in their brains. Using a Wnt agonist delivered by a blood-brain barrier penetrant microglia-specific targeting nanocarrier we prevented in our animal model the pro-inflammatory microglial activation, white matter injury and behavioural deficits. Collectively, these data validate that the Wnt pathway regulates microglial activation, is critical in the evolution of an important form of human brain injury and is a viable therapeutic target.

Polygenic risk for neuropsychiatric disease and vulnerability to abnormal deep grey matter development.

Neuropsychiatric disease has polygenic determinants but is often precipitated by environmental pressures, including adverse perinatal events. However, the way in which genetic vulnerability and early-life adversity interact remains obscure. We hypothesised that the extreme environmental stress of prematurity would promote neuroanatomic abnormality in individuals genetically vulnerable to psychiatric disorders. In 194 unrelated infants (104 males, 90 females), born before 33 weeks of gestation (mean gestational age 29.7 weeks), we combined Magnetic Resonance Imaging with a polygenic risk score (PRS) for five psychiatric pathologies to test the prediction that: deep grey matter abnormalities frequently seen in preterm infants are associated with increased polygenic risk for psychiatric illness. The variance explained by the PRS in the relative volumes of four deep grey matter structures (caudate nucleus, thalamus, subthalamic nucleus and lentiform nucleus) was estimated using linear regression both for the full, mixed ancestral, cohort and a subsample of European infants. Psychiatric PRS was negatively associated with lentiform volume in the full cohort (ß = -0.24, p = 8 × 10-4) and a European subsample (ß = -0.24, p = 8 × 10-3). Genetic variants associated with neuropsychiatric disease increase vulnerability to abnormal lentiform development after perinatal stress and are associated with neuroanatomic changes in the perinatal period.

Machine learning shows association between genetic variability in PPARG and cerebral connectivity in preterm infants.

Preterm infants show abnormal structural and functional brain development, and have a high risk of long-term neurocognitive problems. The molecular and cellular mechanisms involved are poorly understood, but novel methods now make it possible to address them by examining the relationship between common genetic variability and brain endophenotype. We addressed the hypothesis that variability in the Peroxisome Proliferator Activated Receptor (PPAR) pathway would be related to brain development. We employed machine learning in an unsupervised, unbiased, combined analysis of whole-brain diffusion tractography together with genomewide, single-nucleotide polymorphism (SNP)-based genotypes from a cohort of 272 preterm infants, using Sparse Reduced Rank Regression (sRRR) and correcting for ethnicity and age at birth and imaging. Empirical selection frequencies for SNPs associated with cerebral connectivity ranged from 0.663 to zero, with multiple highly selected SNPs mapping to genes for PPARG (six SNPs), ITGA6 (four SNPs), and FXR1 (two SNPs). SNPs in PPARG were significantly overrepresented (ranked 7-11 and 67 of 556,000 SNPs; P < 2.2 × 10-7), and were mostly in introns or regulatory regions with predicted effects including protein coding and nonsense-mediated decay. Edge-centric graph-theoretic analysis showed that highly selected white-matter tracts were consistent across the group and important for information transfer (P < 2.2 × 10-17); they most often connected to the insula (P < 6 × 10-17). These results suggest that the inhibited brain development seen in humans exposed to the stress of a premature extrauterine environment is modulated by genetic factors, and that PPARG signaling has a previously unrecognized role in cerebral development.

Integrative genomics of microglia implicates DLG4 (PSD95) in the white matter development of preterm infants.

Preterm birth places infants in an adverse environment that leads to abnormal brain development and cerebral injury through a poorly understood mechanism known to involve neuroinflammation. In this study, we integrate human and mouse molecular and neuroimaging data to investigate the role of microglia in preterm white matter damage. Using a mouse model where encephalopathy of prematurity is induced by systemic interleukin-1ß administration, we undertake gene network analysis of the microglial transcriptomic response to injury, extend this by analysis of protein-protein interactions, transcription factors and human brain gene expression, and translate findings to living infants using imaging genomics. We show that DLG4 (PSD95) protein is synthesised by microglia in immature mouse and human, developmentally regulated, and modulated by inflammation; DLG4 is a hub protein in the microglial inflammatory response; and genetic variation in DLG4 is associated with structural differences in the preterm infant brain. DLG4 is thus apparently involved in brain development and impacts inter-individual susceptibility to injury after preterm birth.Inflammation mediated by microglia plays a key role in brain injury associated with preterm birth, but little is known about the microglial response in preterm infants. Here, the authors integrate molecular and imaging data from animal models and preterm infants, and find that microglial expression of DLG4 plays a role.

EXPLORING BRAIN TRANSCRIPTOMIC PATTERNS: A TOPOLOGICAL ANALYSIS USING SPATIAL EXPRESSION NETWORKS.

Characterizing the transcriptome architecture of the human brain is fundamental in gaining an understanding of brain function and disease. A number of recent studies have investigated patterns of brain gene expression obtained from an extensive anatomical coverage across the entire human brain using experimental data generated by the Allen Human Brain Atlas (AHBA) project. In this paper, we propose a new representation of a gene's transcription activity that explicitly captures the pattern of spatial co-expression across different anatomical brain regions. For each gene, we define a Spatial Expression Network (SEN), a network quantifying co-expression patterns amongst several anatomical locations. Network similarity measures are then employed to quantify the topological resemblance between pairs of SENs and identify naturally occurring clusters. Using network-theoretical measures, three large clusters have been detected featuring distinct topological properties. We then evaluate whether topological diversity of the SENs reects significant differences in biological function through a gene ontology analysis. We report on evidence suggesting that one of the three SEN clusters consists of genes specifically involved in the nervous system, including genes related to brain disorders, while the remaining two clusters are representative of immunity, transcription and translation. These findings are consistent with previous studies showing that brain gene clusters are generally associated with one of these three major biological processes.

Possible relationship between common genetic variation and white matter development in a pilot study of preterm infants.

BACKGROUND: The consequences of preterm birth are a major public health concern with high rates of ensuing multisystem morbidity, and uncertain biological mechanisms. Common genetic variation may mediate vulnerability to the insult of prematurity and provide opportunities to predict and modify risk. OBJECTIVE: To gain novel biological and therapeutic insights from the integrated analysis of magnetic resonance imaging and genetic data, informed by prior knowledge. METHODS: We apply our previously validated pathway-based statistical method and a novel network-based method to discover sources of common genetic variation associated with imaging features indicative of structural brain damage. RESULTS: Lipid pathways were highly ranked by Pathways Sparse Reduced Rank Regression in a model examining the effect of prematurity, and PPAR (peroxisome proliferator-activated receptor) signaling was the highest ranked pathway once degree of prematurity was accounted for. Within the PPAR pathway, five genes were found by Graph Guided Group Lasso to be highly associated with the phenotype: aquaporin 7 (AQP7), malic enzyme 1, NADP(+)-dependent, cytosolic (ME1), perilipin 1 (PLIN1), solute carrier family 27 (fatty acid transporter), member 1 (SLC27A1), and acetyl-CoA acyltransferase 1 (ACAA1). Expression of four of these (ACAA1, AQP7, ME1, and SLC27A1) is controlled by a common transcription factor, early growth response 4 (EGR-4). CONCLUSIONS: This suggests an important role for lipid pathways in influencing development of white matter in preterm infants, and in particular a significant role for interindividual genetic variation in PPAR signaling.

Systems genetics identifies Sestrin 3 as a regulator of a proconvulsant gene network in human epileptic hippocampus.

Gene-regulatory network analysis is a powerful approach to elucidate the molecular processes and pathways underlying complex disease. Here we employ systems genetics approaches to characterize the genetic regulation of pathophysiological pathways in human temporal lobe epilepsy (TLE). Using surgically acquired hippocampi from 129 TLE patients, we identify a gene-regulatory network genetically associated with epilepsy that contains a specialized, highly expressed transcriptional module encoding proconvulsive cytokines and Toll-like receptor signalling genes. RNA sequencing analysis in a mouse model of TLE using 100 epileptic and 100 control hippocampi shows the proconvulsive module is preserved across-species, specific to the epileptic hippocampus and upregulated in chronic epilepsy. In the TLE patients, we map the trans-acting genetic control of this proconvulsive module to Sestrin 3 (SESN3), and demonstrate that SESN3 positively regulates the module in macrophages, microglia and neurons. Morpholino-mediated Sesn3 knockdown in zebrafish confirms the regulation of the transcriptional module, and attenuates chemically induced behavioural seizures in vivo.

Common genetic variants and risk of brain injury after preterm birth.

BACKGROUND: The role of heritable factors in determining the common neurologic deficits seen after preterm birth is unknown, but the characteristic phenotype of neurocognitive, neuroanatomical, and growth abnormalities allows principled selection of candidate genes to test the hypothesis that common genetic variation modulates the risk for brain injury. METHODS: We collected an MRI-linked genomic DNA library from 83 preterm infants and genotyped tag single nucleotide polymorphisms in 13 relevant candidate genes. We used tract-based spatial statistics and deformation-based morphometry to examine the risks conferred by carriage of particular alleles at tag single nucleotide polymorphisms in a restricted number of genes and related these to the preterm cerebral endophenotype. RESULTS: Carriage of the minor allele at rs2518824 in the armadillo repeat gene deleted in velocardiofacial syndrome (ARVCF) gene, which has been linked to neuronal migration and schizophrenia, and rs174576 in the fatty acid desaturase 2 gene, which encodes a rate-limiting enzyme for endogenous long chain polyunsaturated fatty acid synthesis and has been linked to intelligence, was associated with white matter abnormality measured in vivo using diffusion tensor imaging (P = .0009 and P = .0019, respectively). CONCLUSIONS: These results suggest that genetic variants modulate white matter injury after preterm birth, and known susceptibilities to neurologic status in later life may be exposed by the stress of premature exposure to the extrauterine environment.

Expression profiling of mouse subplate reveals a dynamic gene network and disease association with autism and schizophrenia.

The subplate zone is a highly dynamic transient sector of the developing cerebral cortex that contains some of the earliest generated neurons and the first functional synapses of the cerebral cortex. Subplate cells have important functions in early establishment and maturation of thalamocortical connections, as well as in the development of inhibitory cortical circuits in sensory areas. So far no role has been identified for cells in the subplate in the mature brain and disease association of the subplate-specific genes has not been analyzed systematically. Here we present gene expression evidence for distinct roles of the mouse subplate across development as well as unique molecular markers to extend the repertoire of subplate labels. Performing systematic comparisons between different ages (embryonic days 15 and 18, postnatal day 8, and adult), we reveal the dynamic and constant features of the markers labeling subplate cells during embryonic and early postnatal development and in the adult. This can be visualized using the online database of subplate gene expression at https://molnar.dpag.ox.ac.uk/subplate/. We also identify embryonic similarities in gene expression between the ventricular zones, intermediate zone, and subplate, and distinct postnatal similarities between subplate, layer 5, and layers 2/3. The genes expressed in a subplate-specific manner at some point during development show a statistically significant enrichment for association with autism spectrum disorders and schizophrenia. Our report emphasizes the importance of the study of transient features of the developing brain to better understand neurodevelopmental disorders.

Diffusion features of white matter in tuberous sclerosis with tractography.

Normal-appearing white matter has been shown via diffusion tensor imaging to be affected in tuberous sclerosis complex. Under the hypothesis that some systems might be differentially affected, including the visual pathways and systems of social cognition, diffusion properties of various regions of white matter were compared. For 10 patients and 6 age-matched control subjects, 3 T magnetic resonance imaging was assessed using diffusion tensor imaging obtained in 35 directions. Three-dimensional volumes corresponding to the geniculocalcarine tracts were extracted via tractography, and two-dimensional regions of interest were used to sample other regions. Regression analysis indicated lower fractional anisotropy in the splenium of corpus callosum and geniculocalcarine tracts in tuberous sclerosis complex group, as well as lower axial diffusivity in the internal capsule, superior temporal gyrus, and geniculocalcarine tracts. Mean and radial diffusivity of the splenium of corpus callosum were higher in the tuberous sclerosis complex group. The differences in diffusion properties of white matter between tuberous sclerosis complex patients and control subjects suggest disorganized and structurally compromised axons with poor myelination. The visual and social cognition systems appear to be differentially involved, which might in part explain the behavioral and cognitive characteristics of the tuberous sclerosis complex population.

Relationship between white matter apparent diffusion coefficients in preterm infants at term-equivalent age and developmental outcome at 2 years.

OBJECTIVE: The aim of this study was to develop a simple reproducible method for the measurement of apparent diffusion coefficient values in the white matter of preterm infants using diffusion-weighted imaging to test the hypothesis that elevated mean apparent diffusion coefficient values are associated with lower developmental quotient scores at 2 years' corrected age. METHODS: We obtained diffusion-weighted imaging in 38 preterm infants at term-equivalent age who had no evidence of overt cerebral pathology on conventional MRI. Mean apparent diffusion coefficient values at the level of the centrum semiovale were determined. The children were assessed using a standardized neurologic examination, and the Griffiths Mental Development Scales were administered to obtain a developmental quotient at 2 years' corrected age. The relationship between mean apparent diffusion coefficient values and developmental quotient was examined. Clinical data relating to postnatal sepsis, antenatal steroid exposure, supplemental oxygen, gender, patent ductus arteriosus, and inotrope requirement were collected, and the mean apparent diffusion coefficient values for each group were compared. RESULTS: The mean (+/-SD) apparent diffusion coefficient value in the white matter was 1.385 +/- 0.07 x 10(-3) mm2/second, and the mean developmental quotient was 108.9 +/- 11.5. None of the children had a significant neurologic problem. There was a significant negative correlation between mean apparent diffusion coefficient and developmental quotient. CONCLUSION: These findings suggest that higher white matter apparent diffusion coefficient values at term-equivalent age in preterm infants without overt lesions are associated with poorer developmental performance in later childhood. Consequently, apparent diffusion coefficient values at term may be of prognostic value for neurodevelopmental outcome in infants who are born preterm and who have no other imaging indicators of abnormality.