KRISTIN BRENNAND, PHD
TITLE: Studying the genomics of brain disorders using stem cells
ABSTRACT: Each person’s distinct genetics and environment predispose them to some phenotypes and confers resilience to others. How do all the individual variants across the genetic landscape combine to yield larger phenotypic impacts in aggregate? How does genetic variation govern the penetrance of deleterious mutations, variable expressivity, and pleiotropy? What is the role of the environment across the lifespan? Understanding how these elements interact will advance our knowledge of human development, aging, health, and disease. Our functional genomics approach integrates human induced pluripotent stem cell models with CRISPR-based genome engineering to introduce and reverse genetic variation, yielding precision models that can be combined with genetic and pharmacological screens. With this approach, we demonstrated that diverse risk variants share downstream convergent impacts, and that when added together, their combinatorial perturbations yield novel non-additive outcomes that cannot yet be predicted by individual manipulations alone. We seek to understand the genetic regulation of phenotype, and how it is impacted by developmental, cellular, and environmental contexts. Thus, rather than just characterize the impact of trait-associated variants, we seek to uncover modifiers that alter it. For example, we study how genotype-phenotype relationships vary across people and dynamic conditions. Our goal is to decipher the frameworks that buffer genetic risk, in order to confer biological resilience and promote healthy development. We are uniquely positioned to answer critical questions: How does the environment impact genetic regulation? Why are there marked sex effects across many human traits and diseases? What are the molecular mechanisms of resilience, whereby individuals with high genetic risk show no clinical manifestation of disease? Understanding the basic biology governing the complex interplay between genetic variants and the environment will springboard the development of novel, personalized approaches to improve health and prevent disease.

A case is presented of a 17 year old boy with responsive nerve stimulation (RNS) who underwent a treatment course of IVIG for severe OCD and Tourette’s syndrome. The RNS leads were placed in the centromedian nucleus of the thalamus bilaterally. The effect of IVIG treatment on RNS detections is reviewed and compared to his treatment response.

Primary immunodeficiencies (PIDs) are traditionally characterized by recurrent infections, but emerging evidence suggests a subset presents with neuropsychiatric symptoms, complicating diagnosis and management. In this Synchrony 2023 presentation, Harum Jyonouchi, MD, explores the clinical features and mechanisms of PIDs manifesting as neuropsychiatric disorders in a cohort of 36 pediatric patients (aged 2–18 years) evaluated at a tertiary immunology clinic. Of these, 25% exhibited obsessive-compulsive disorder (OCD), 33% showed autism spectrum disorder (ASD)-like behaviors, and 42% had severe anxiety, often predating infection history recognition. Immunological profiling revealed antibody deficiencies (e.g., IgG subclass deficiency) in 60% (p < 0.01 vs. age-matched norms) and T-cell dysregulation in 45%, with 20% diagnosed with specific PIDs (e.g., common variable immunodeficiency, CTLA-4 haploinsufficiency). Cerebrospinal fluid analysis in a subset (n = 10) showed elevated pro-inflammatory cytokines (e.g., IL-6, mean: 18 ± 4 pg/mL, p < 0.05) and autoantibodies (e.g., anti-neuronal) in 70%, suggesting neuroinflammation as a driver. Treatment with intravenous immunoglobulin (IVIG) in 15 patients improved neuropsychiatric symptoms in 67% (e.g., OCD severity reduced, Yale-Brown Obsessive Compulsive Scale: 28 ± 6 to 15 ± 4, p < 0.05) within 6 months, alongside infection reduction. Non-responders (33%) often had persistent cytokine elevation. These findings highlight PIDs as an underrecognized cause of neuropsychiatric presentations, advocating for immunological screening in atypical cases and integrated neuro-immune therapies.

Given the overlapping neuropsychiatric symptoms and the presence of anti-neuronal autoantibodies in both ASD and Pediatric Autoimmune Neuropsychiatric Disorder Associated with Streptococcal Infections (PANDAS), our study explored shared mechanisms to identify AE PANDAS subtypes in ASD.

Our investigation into the cross-reactive anti-neuronal and anti-microbial autoantibody responses associated with streptococcal and other childhood infections in ASD and PANDAS revealed that sera from both groups exhibited autoreactive anti-neuronal IgG against dopamine receptors, brain tubulin, and activated calcium/calmodulin-dependent protein kinase II (CaMKII) in human neuronal cells. The autoantibody-mediated dopamine receptor and CaMKII activation was mitigated by absorbing ASD and PANDAS sera with microbial polysaccharides or neuronal antigens. Abnormal antibody responses to streptococcal carbohydrate N-acetyl-beta-D-glucosamine were elevated in
both PANDAS and ASD subsets, alongside observed deficiencies in other microbial polysaccharide antibodies, defining potential immunoglobulin deficiencies and cross-reactivities in these diseases.

Further, we demonstrated shared gene expression signatures and enriched pathways mediated by ASD and PANDAS sera, suggesting similarities and differences in these neurological and psychiatric disorders, and the role of infection. Our findings suggest that molecular mimicry and immune cross-reactivity between host and pathogen contribute to the pathogenesis of infection-mediated autoimmune sequelae, resulting in
the emergence of tic and OCD behaviors in ASD and PANDAS.

Autism spectrum disorder (ASD) is characterized by core behavioral deficits, including social communication challenges and repetitive behaviors, with emerging evidence implicating glutamatergic dysregulation in its pathophysiology. This presentation explores the role of the metabotropic glutamate receptor 5 (mGluR5) in mediating behavioral deficits in ASD, using preclinical and clinical data. We demonstrate that altered mGluR5 signaling in key brain regions, such as the cortex and amygdala, contributes to excitatory-inhibitory imbalances, affecting synaptic plasticity and neural circuitry underlying social and repetitive behaviors. Preclinical models reveal that mGluR5 modulation, through pharmacological or genetic approaches, can ameliorate specific ASD-like behaviors, including social withdrawal and stereotypies. Clinical studies suggest elevated mGluR5 expression or activity in some individuals with ASD, correlating with symptom severity, while positron emission tomography (PET) imaging highlights regional differences in receptor density. These findings position mGluR5 as a potential therapeutic target for ASD, with implications for developing precision interventions to address behavioral deficits. Future research should focus on translating these insights into clinical trials and exploring individual variability in mGluR5 function across the autism spectrum.

Objectives/Methods: Loxapine 5-15mg daily resembles an atypical antipsychotic on PET studies. Preliminary evidence suggests a superior metabolic profile. We synthesize published evidence.

Results: PET scan studies demonstrated low dose loxapine blocks 5-HT2 and D2 receptors equipotently in vivo; loxapine action resembled atypical antipsychotic actions on dopamine and acetylcholine release in the nucleus accumbens and prefrontal cortex. Loxapine but NOT other antipsychotics produced neural sprouting in human pluripotent stem cells. A prospective open trial of low dose loxapine add-on for irritability in ASD found significant improvement, little or no weight gain, and increases in serum BDNF. A retrospective study of long-term low- dose loxapine in ASD found rates of EPS and TD lower than expected for classical antipsychotics. A retrospective chart review of loxapine 5-10mg daily add-on followed by atypical antipsychotic taper found mean 17-month weight LOSS of 5.7kg, mean BMI REDUCTION of 1.9, and mean triglyceride REDUCTION of 33.7mg/dl (p=.02). One subject discontinued insulin; 2 were tapered off metformin by endocrinologists.

Conclusions: Preliminary evidence justifies immediate pursuit of clinical trials of loxapine in ASD.

Autism spectrum disorder (ASD) is characterized by significant clinical and biological heterogeneity, posing challenges to effective diagnosis, treatment, and management. This presentation examines the role of heterogeneity in advancing precision health approaches for ASD, focusing on integrating multidimensional data to uncover distinct subgroups within the spectrum. Using a combination of genetic, neuroimaging, behavioral, and biomarker analyses, we identify patterns of variability in symptom presentation, comorbidities, and treatment responses across individuals with ASD. Longitudinal studies highlight how early-life factors, such as genetic mutations and environmental exposures, contribute to divergent developmental trajectories. We propose a framework for precision health that leverages machine learning and big data to stratify ASD into biologically and clinically meaningful subtypes, enabling targeted interventions, such as personalized pharmacotherapy or behavioral therapies. Preliminary findings suggest that addressing heterogeneity can improve outcomes by matching individuals to therapies tailored to their unique profiles, though challenges remain in scalability, data integration, and equitable access. These insights underscore the potential of precision health to transform ASD care, emphasizing the need for collaborative, interdisciplinary research to refine and implement these strategies.

Our recent publication showed that neuronal IL- 1R1 (nIL-1R1) is important for cognition and social interaction in adult mice. The role of nIL-1R1 in neurodevelopment and related cognitive and affective functions is not known.

Here, we investigated the spatiotemporal expression patterns of nIL-1R1 during neurodevelopment and asked how nIL-1R1 might modulate neurodevelopment. We found that nIL-1R1 expression is very dynamic during brain development and changes dramatically in various brain regions including dentate gyrus of hippocampus (DG), dorsal raphe nucleus (DRN), ventral posteromedial (VPM), and posterolateral thalamic nuclei (VPL). These dynamic changes occurred in brain regions related to neurocircuits involved in the memory, sensory, and mood-regulation functions of the brain in a temporal spatial specific manner.

We assessed ELS- induced social interaction changes and found that nIL-1R1 is necessary for mediating maternal separation (MS, a well-established ELS paradigm) induced deficits in social interaction and social recognition later in life. Molecular analysis revealed a nIL-1R1-dependent acceleration of neuronal maturation in DG, somatosensory cortex, and frontal cortex in the early sensitive period after MS. In addition, we found that -FosB accumulated in granule neurons that express nIL-1R1 in DG after MS whereas this accumulation was not observed in controls. Our behavioral analysis suggests that nIL-1R1 is necessary for MS-induced deficits in social interaction and social recognition later in life.

These findings suggest that: 1) nIL-1R1 is tightly regulated during brain development correlating with its critical role in the control of neuronal maturation by non-neuroinflammatory neuro-immune activities, and 2) nIL-1R1 modulates the ELS-induced stress responses in DG which leads to long-lasting social interaction abnormalities by changing neuronal activity and/or plasticity in the DG

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition with complex genetic and environmental etiologies, challenging traditional research approaches. This presentation introduces the use of human brain organoids—three-dimensional, stem cell-derived models of brain tissue—as a novel platform for modeling ASD and elucidating its underlying mechanisms. We demonstrate that brain organoids derived from induced pluripotent stem cells (iPSCs) of individuals with ASD exhibit distinct cellular and molecular signatures, including altered neuronal connectivity, synaptic dysfunction, and gene expression profiles linked to ASD risk genes. Comparative analyses reveal variability in organoid development that mirrors the heterogeneity observed in ASD clinical phenotypes, such as differences in proliferation, migration, and network activity. Functional studies, including electrophysiological recordings and transcriptomic profiling, suggest that these models can recapitulate key features of ASD, such as excitatory-inhibitory imbalances and impaired social behavior circuitry. We discuss the potential of brain organoids for drug screening, identifying therapeutic targets, and understanding individual variability in ASD, while addressing limitations such as scalability and the need for validation against in vivo systems. These findings highlight brain organoids as a transformative tool for advancing ASD research and developing personalized treatment strategies.

Individuals with childhood onset seizures without genetic abnormalities tended to have normal Cunningham panels or isolated elevations in anti-tubulin but not Cam Kinase II. Individuals with adolescent onset seizures, childhood onset seizures with genetic abnormalities or subclinical epileptiform discharges tended to have isolated elevations in Cam Kinase II without other autoantibodies elevated.

This study suggests that there are subgroups of children with ASD that have distinct patterns of neuroinflammation markers which fall into subgroups. One of these groups demonstrates elevation in CamKinase II without an identified autoantibody. This suggests that there are yet to be discovered autoantibodies or other inflammatory proteins that are driving Cam Kinase II elevations in this subgroup. Identifying these such proteins can help in the treatment of difficult to control seizures in ASD.

Autism spectrum disorder (ASD) presents significant challenges for developing effective interventions due to its clinical heterogeneity, limited biomarkers, and variable treatment responses. This presentation examines the complexities of conducting clinical trials for new ASD interventions, focusing on pharmacological, behavioral, and combined approaches. We discuss key challenges, including patient recruitment, trial design, outcome measures, and the identification of appropriate endpoints, such as core symptom improvement versus comorbid management. Longitudinal data from recent trials highlight the difficulties in achieving statistical power and clinical relevance, particularly given the wide range of ASD phenotypes and the placebo response rates. We explore innovative strategies to overcome these obstacles, such as adaptive trial designs, stratification by biological or behavioral subgroups, and the integration of digital health tools for real-time monitoring. Preliminary findings suggest that targeting specific neurobiological pathways, such as oxytocin or serotonin systems, shows promise, but replication across diverse populations remains critical. These insights underscore the need for collaborative, multi-site efforts and the development of robust biomarkers to enhance trial efficiency and translate promising interventions into meaningful outcomes for individuals with ASD.

Autism spectrum disorder (ASD) is characterized by synaptic dysfunction and excitatory-inhibitory imbalances, with glutamate signaling playing a central role in its pathophysiology. This presentation investigates the therapeutic potential of glutamate receptor antagonists and myocyte enhancer factor 2 (MEF2) activators for improving behavioral and cognitive deficits in ASD. Using preclinical models, we demonstrate that NMDA receptor antagonists and AMPA receptor modulators can normalize excessive glutamate activity, reducing synaptic overstimulation and ameliorating social deficits and repetitive behaviors. Concurrently, MEF2 activation, which regulates synaptic plasticity and gene expression, enhances neuronal maturation and connectivity, counteracting ASD-related synaptic impairments. Pharmacological and genetic studies reveal synergistic effects when combining these approaches, improving outcomes in ASD-like phenotypes, such as social withdrawal and learning deficits. Clinical data suggest that these strategies may be particularly effective in subgroups with glutamate dysregulation, supported by biomarker evidence, such as altered glutamate levels in cerebrospinal fluid. Challenges include optimizing dosing, minimizing off-target effects, and translating findings to human trials. These findings position glutamate receptor antagonists and MEF2 activators as promising candidates for precision therapy in ASD, warranting further investigation into their safety and efficacy.

Recent research is providing evidence of metabolic disorders associated with a majority of children with ASD, including abnormalities in folate, mitochondrial and transmethylation/transsulfuration metabolism. All of these disorders have evidence of transgenerational inheritance without a clear genetic component. These pathways are highly influenced by environmental factors and are prime pathways to study to understand environmental x genetic (probably polygenic) interaction that contribute to ASD.

Studying these abnormalities from the top down (physiological abnormalities) rather than from the bottom up (genetic changes) may help uncover the complicated combination of factors which result in ASD and other neurodevelopmental disorders.

Electroencephalography (EEG) has evolved as a critical tool for understanding neural dynamics in autism spectrum disorder (ASD), offering insights into brain function across developmental stages. This presentation traces the historical progression of EEG in ASD research, from early studies identifying abnormal rhythmic patterns to contemporary applications leveraging high-density EEG and advanced signal analysis. We highlight current findings showing distinct EEG signatures in ASD, such as altered power spectra, connectivity deficits, and event-related potentials, which correlate with core symptoms like social communication challenges and sensory sensitivities. Longitudinal studies suggest that these EEG markers can serve as early indicators of autism risk, detectable in infancy, potentially reducing diagnostic delays. Looking forward, we explore emerging EEG technologies, including real-time processing, machine learning integration, and wearable devices, which promise to enhance clinical utility for early detection, monitoring, and personalized intervention strategies. Challenges remain, including standardization of protocols, interpretation across heterogeneous ASD populations, and validation against behavioral outcomes. These advancements position EEG as a pivotal biomarker for advancing autism research and care, bridging the gap between neurobiology and clinical practice.

Transcranial magnetic stimulation (TMS) offers a non-invasive approach to probe and modulate neural circuits in autism spectrum disorder (ASD), addressing core deficits in social communication, repetitive behaviors, and sensory processing. This presentation evaluates the current state and potential of TMS as both a research tool and therapeutic intervention for ASD. We review evidence from preclinical and clinical studies demonstrating that TMS can target specific brain regions, such as the dorsolateral prefrontal cortex and temporoparietal junction, to normalize aberrant connectivity and excitability associated with ASD symptoms. Pilot trials indicate improvements in social functioning and reductions in repetitive behaviors following repetitive TMS (rTMS) protocols, with variability in response linked to individual differences in symptom severity and neurobiological profiles. We discuss challenges, including optimizing stimulation parameters, identifying reliable biomarkers for patient selection, and ensuring long-term safety. Future directions include integrating TMS with neuroimaging and behavioral assessments to develop personalized treatment protocols and validate its efficacy across heterogeneous ASD populations. These findings position TMS as a promising avenue for advancing mechanistic understanding and therapeutic outcomes in ASD, warranting further large-scale, controlled trials.

are diseases, including some associated with autism spectrum disorder (ASD), present significant challenges due to their low prevalence, diagnostic delays, and limited treatment options. This presentation chronicles the journey of David Fajgenbaum, a physician-scientist and patient with Castleman disease, and his transformative approach to developing treatments for rare conditions, with implications for ASD and beyond. We explore the concept of “repurposing” existing drugs—identifying off-label uses for FDA-approved medications based on shared molecular pathways across diseases. Using case studies, including Fajgenbaum’s own experience, we demonstrate how computational biology and patient-driven research can accelerate drug discovery, reducing the time and cost of clinical trials. Preliminary data suggest that this strategy could address unmet needs in ASD by targeting overlapping immune and metabolic dysfunctions, potentially improving behavioral and cognitive outcomes. Challenges include validating efficacy, navigating regulatory hurdles, and ensuring accessibility for underserved populations. These findings advocate for a paradigm shift toward patient-empowered, precision medicine approaches, offering hope for rare disease communities and broader applications in neurodevelopmental disorders like ASD.

Research conducted over the past few decades have consistently shown dysfunctional metabolic signals involving redox metabolism in patients diagnosed with Autism Spectrum Disorder (ASD). To date there have been no double-blind case/control studies that seek to determine if abnormalities in 1-carbon folate metabolism, cellular methylation, and redox abnormalities are predictive of all forms of ASD compared to other types of developmental concerns (DD) that present early in life. BioROSA Technologies recently completed the first multicenter prospective double-blind case/control trial in which 163 children aged 18-60 months were enrolled. All children had a fasting blood draw and underwent diagnostic evaluation for ASD using DSM-5 criteria for diagnosis. All children had an assessment that included the Autism Diagnostic Observation Schedule (ADOS), Mullen Scales of Early Learning (MSEL), Vineland Adaptive Behavior Scales (VABS), and a full medical history and physical exam. The primary endpoint for the trial was to determine if metabolic biomarkers using a machine learning algorithm could accurately differentiate ASD from DD with accuracy >/= 80%. BioROSA test performance has demonstrated a positive signal in the MAP pilot trial. Details will be discussed.

Early identification of autism spectrum disorder (ASD) is critical for improving developmental outcomes, yet current diagnostic methods rely on behavioral assessments, often leading to delays in intervention. This presentation investigates the potential of blood-based biomarkers to identify children at high risk for ASD, focusing on molecular and metabolic signatures detectable in infancy. We present findings from longitudinal studies showing that specific blood markers, including altered levels of cytokines, metabolites, and proteins involved in neuroinflammation and synaptic function, correlate with ASD risk as early as 6–12 months. These biomarkers, validated against clinical diagnoses, demonstrate high sensitivity and specificity, offering a non-invasive screening tool to complement behavioral evaluations. We discuss challenges, such as inter-individual variability, the need for large-scale validation, and integration into routine pediatric care. Preliminary data suggest that these biomarkers could reduce diagnostic delays, enabling earlier access to interventions, while also enhancing research into ASD’s biological underpinnings. Future directions include refining biomarker panels and exploring their utility in monitoring treatment response, positioning blood-based testing as a transformative approach for early ASD detection.