Michela Fagiolini

Background: Rett syndrome (RTT), a rare neurodevelopmental disorder caused primarily by pathogenic variants in the MECP2 gene, is characterized by severe cognitive, motor, and autonomic impairments. Atypical sensory processing—including co-occurring hypo- and hyper-responsivity—is a core yet poorly understood feature. While evoked potentials (EPs) show delayed and attenuated sensory responses in RTT, the underlying mechanisms of these impairments remain unclear. Inter-trial phase coherence (ITPC), which quantifies trial-by-trial neural response consistency, offers a promising functional biomarker of variability in sensory processing. Methods: We characterized caregiver-reported sensory responsivity in 32 individuals with RTT (all female) and 28 typically developing controls (26 female, 2 male). EPs were then recorded during passive visual and auditory stimulation and ITPC was computed to assess whether variability in the timing of neural responses could account for reduced EP amplitudes and atypical sensory responsivity. Results: Hypo- and hyper-responsivity to sensory stimuli were both significantly elevated in RTT and were positively correlated, co-occurring within individuals. ITPC was significantly reduced in RTT across visual and auditory modalities and was associated with reduced EP amplitudes. Notably, reduced ITPC in visual-evoked potentials was further associated with elevated visual responsivity and greater behavioral symptom severity. Conclusions: Increased variability in neural response timing may contribute to both reduced EPs and atypical sensory responsivity in RTT, supporting ITPC as a functional biomarker. Decreased temporal precision of neural activity may explain the co-occurrence of hypo- and hyper-responsivity and provide a unifying framework for sensory dysfunction across neurodevelopmental disorders.

Human cerebral organoids derived from induced pluripotent stem cells can recapture early developmental processes and reveal changes involving neurodevelopmental disorders. Mutations in the X-linked methyl-CpG binding protein 2 (MECP2) gene are associated with Rett syndrome, and disease severity varies depending on the location and type of mutation. Here, we focused on neuronal activity in Rett syndrome patient-derived organoids, analyzing two types of MECP2 mutations—a missense mutation (R306C) and a truncating mutation (V247X)—using calcium imaging with three-photon microscopy. Compared to isogenic controls, we found abnormal neuronal activity in Rett organoids and altered network function based on graph theoretic analyses, with V247X mutations impacting functional responses and connectivity more severely than R306C mutations. These changes paralleled EEG data obtained from patients with comparable mutations. Labeling >/>DLX promoter-driven inhibitory neurons demonstrated differences in activity and functional connectivity of inhibitory and excitatory neurons in the two types of mutations. Transcriptomic analyses revealed HDAC2-associated impairment in R306C organoids and decreased GABA_A receptor expression in excitatory neurons in V247X organoids. These findings demonstrate mutation-specific mechanisms of vulnerability in Rett syndrome and suggest targeted strategies for their treatment.

TECPR2 -related disorder is a rare, autosomal recessive neurodevelopmental and neurodegenerative disease characterized by early-onset motor dysfunction, sensory- and autonomic neuropathy, and progressive neurological decline with early mortality. Currently, there are no effective treatments for individuals affected by this debilitating condition. To advance our understanding of disease mechanisms and explore therapeutic strategies, we developed and then characterized a knock-in (KI) mouse model carrying the human TECPR2 c.1319delC frameshift mutation. TECPR2-KI mice exhibit a subset of disease-relevant phenotypes, most prominently abnormal gait, along with reduced body weight and altered tactile sensitivity. We additionally observe a reduction in acoustic startle responses, consistent with dysfunction of brainstem-associated sensorimotor pathways. Histopathological analyses reveal progressive accumulation of axonal spheroids in the dorsal column nuclei, together with abnormalities in autophagy-related markers, features previously reported in individuals with TECPR2 -related disorder. To assess the therapeutic potential of gene replacement, we delivered TECPR2 via intracisternal infusion of AAV9/ TECPR2 in neonatal KI mice. Gene therapy restored mechanosensory function, normalized gait and startle responses, maintain autophagic homeostasis, and partially reduced axonal pathology. These findings demonstrate that TECPR2 -associated deficits are not only replicable in this new mouse model but are also amenable to postnatal intervention. Our study introduces a genetically accurate murine model of TECPR2 deficiency, identifies brainstem-associated phenotypes, and provides preliminary evidence supporting the feasibility of AAV9-mediated TECPR2 gene delivery, establishing a foundation for future translational research in a currently untreatable disease. One-Sentence Key Message: TECPR2 deficiency disrupts brainstem sensory–motor circuits, impairing autophagy and tactile, gait, and startle function and is prevented by neonatal AAV9.

Objective: Rett syndrome (RTT) is a devastating neurodevelopmental disorder with developmental regression affecting motor, sensory, and cognitive functions. Sensory disruptions contribute to the complex behavioral and cognitive difficulties and represent an important target for therapeutic interventions. Although genetic medicine‐based therapies targeting MeCP2 have successfully restored motor and respiratory functions in animal models, their ability to reverse sensory deficits across levels of the visual pathway remains largely unexplored. Methods: Using genetically reversible mouse models of MeCP2 deficiency (Mecp2 ^stop/y and Mecp2 ^stop/x ), we applied advanced electrophysiological, anatomical, and behavioral techniques to evaluate visual function, a critical sensory domain impaired in both animal models and RTT patients. Results: In Mecp2 ^stop/y mice, initiating MeCP2 expression after postnatal day 35 (P35) reversed progressive cortical dysfunction, prevented thalamic circuit disorganization, and restored visual function, despite some remaining cortical anatomical abnormalities. Even in fully regressed adult Mecp2 ^stop/x heterozygous female mice, MeCP2 reactivation was sufficient to reduce the symptoms. Interpretation: These findings highlight the remarkable sensitivity of cortical circuits to MeCP2 expression in both developing and mature brain. Importantly, restoring just 60%–70% of MeCP2 protein levels was sufficient to rescue sensory functions, even after the onset of regression. This underscores the transformative potential of genetic medicine‐based therapies in RTT, suggesting that even partial restoration of MeCP2 can meaningfully improve sensory processing and quality of life for patients.

Rett syndrome is a rare neurodevelopmental disorder caused primarily by pathogenic variants in the MECP2 gene, leading to lifelong cognitive impairments. To understand the broad neural disruptions in Rett syndrome, it is essential to examine large-scale brain dynamics at the level of neural oscillations. Phase-amplitude coupling—a form of cross-frequency interaction that supports information integration across temporal and spatial scales—is a promising candidate measure for capturing such widespread neural dysfunction. Phase-amplitude coupling depends on the coordinated activity of specific neuronal subtypes, and while multiple subtypes are implicated in different aspects of the Rett syndrome phenotype, their role in shaping large-scale oscillatory dynamics in Rett syndrome is not well understood. To investigate this, we utilized a multi-level approach, combining EEG recordings with computational modeling to identify alterations in phase-amplitude coupling in Rett syndrome and probe their underlying cellular and circuit-level mechanisms. We recorded resting-state EEG from 38 individuals with Rett syndrome and 30 age- and sex-matched typically developing individuals. Phase-amplitude coupling was quantified: modulation index was obtained to determine coupling strength, and phase bias was assessed to examine the preferred phase of coupling. We characterized phase-amplitude coupling across all low and high frequency combinations and electrodes, as well as within canonical theta-gamma and alpha-gamma frequency pairs across four predefined cortical regions. Finally, we modeled a biophysically-constrained Layer 4 cortical network to propose a possible mechanism underlying changes to oscillatory dynamics. We found significantly stronger phase-amplitude coupling in Rett syndrome across widespread cortical regions and frequency pairs, with a pronounced increase in theta-gamma and alpha-gamma coupling in anterior, posterior, and whole-brain regions ( P < 0.05). Individuals with Rett syndrome also exhibited a more positive alpha-gamma phase bias in anterior and whole-brain regions ( P < 0.05). Biophysically constrained modelling demonstrated that reduced VIP-expressing interneuron activity alone could recapitulate the pattern of increased theta-gamma and alpha-gamma phase-amplitude coupling observed in Rett syndrome ( P < 0.001). These findings identify alterations in awake-state phase-amplitude coupling in Rett syndrome and propose a mechanistic link to VIP+ interneuron dysfunction. Elevated phase-amplitude coupling may serve as a promising biomarker of cortical dysfunction and a translational bridge from neural circuitry to clinically observable EEG signatures. By implicating VIP+ interneurons, our results open new avenues for testing interventions in preclinical models to identify potential novel therapeutic targets for individuals with Rett syndrome.

Functional and structural connectivity alterations in short- and long-range projections have been reported across neurodevelopmental disorders (NDD). Interhemispheric callosal projection neurons (CPN) represent one of the major long-range projections in the brain, which are particularly important for higher-order cognitive function and flexibility. However, whether a causal relationship exists between interhemispheric connectivity alterations and cognitive deficits in NDD remains elusive. Here, we focused on CDKL5 Deficiency Disorder (CDD), a severe neurodevelopmental disorder caused by mutations in the X-linked Cyclin-dependent kinase-like 5 (CDKL5) gene. We found an increase in homotopic interhemispheric connectivity and functional hyperconnectivity across higher cognitive areas in adult male and female CDKL5-deficient mice by resting-state functional MRI (rs-fMRI) analysis. This was accompanied by an increase in the number of callosal synaptic inputs but decrease in local synaptic connectivity in the cingulate cortex of juvenile CDKL5-deficient mice, suggesting an impairment in excitatory synapse development and a differential role of CDKL5 across excitatory neuron subtypes. These deficits were associated with significant cognitive impairments in CDKL5 KO mice. Selective deletion of CDKL5 in the largest subtype of CPN likewise resulted in an increase of functional callosal inputs, without however significantly altering intracortical cingulate networks. Notably, such callosal-specific changes were sufficient to cause cognitive deficits. Finally, when CDKL5 was selectively re-expressed only in this CPN subtype, in otherwise CDKL5-deficient mice, it was sufficient to prevent the cognitive impairments of CDKL5 mutants. Together, these results reveal a novel role of CDKL5 by demonstrating that it is both necessary and sufficient for proper CPN connectivity and cognitive function and flexibility, and further validates a causal relationship between CPN dysfunction and cognitive impairment in a model of NDD.

Spontaneous pupil size fluctuations in humans and mouse models are noninvasively measured data that can be used for early detection of neurodevelopmental spectrum disorders. While highly valuable in such applied studies, pupillometry dynamics and dynamical characteristics have not been fully investigated, although their understanding may potentially lead to the discovery of new information, which cannot be readily uncovered by conventional methods. Properties of pupillometry dynamics, such as determinism, were previously investigated for healthy human subjects; however, the dynamical characteristics of pupillometry data in mouse models, and whether they are similar to those of human subjects, remain largely unknown. Therefore, it is necessary to establish a thorough understanding of the dynamical properties of mouse pupillometry dynamics and to clarify whether it is similar to that of humans. In this study, dynamical pupillometry characteristics from 115 wild-type mouse datasets were investigated by methods of nonlinear time series analysis. Results clearly demonstrated a strong underlying determinism in the investigated data. Additionally, the data’s trajectory divergence rate and predictability were estimated.

Autism Spectrum Disorder (ASD) is characterized by substantial, yet highly heterogeneous abnormalities in functional brain connectivity. However, the origin and significance of this phenomenon remain unclear. To unravel ASD connectopathy and relate it to underlying etiological heterogeneity, we carried out a bi-center cross-etiological investigation of fMRI-based connectivity in the mouse, in which specific ASD-relevant mutations can be isolated and modeled minimizing environmental contributions. By performing brain-wide connectivity mapping across 16 mouse mutants, we show that different ASD-associated etiologies cause a broad spectrum of connectional abnormalities in which diverse, often diverging, connectivity signatures are recognizable. Despite this heterogeneity, the identified connectivity alterations could be classified into four subtypes characterized by discrete signatures of network dysfunction. Our findings show that etiological variability is a key determinant of connectivity heterogeneity in ASD, hence reconciling conflicting findings in clinical populations. The identification of etiologically-relevant connectivity subtypes could improve diagnostic label accuracy in the non-syndromic ASD population and paves the way for personalized treatment approaches.