Advances in data-driven approaches to parsing ASD heterogeneity are synthesized and a simple one-to-one correspondence between behavioral and neural subtypes are argued; instead, the evidence is more consistent with multi-to-one, one-to-many, or many-to-many mappings that converge on the overall functional impairment.
Abstract
Autism spectrum disorder (ASD) exhibits pronounced heterogeneity across genetic, neurobiological, and clinical phenotypic levels, posing substantial challenges for mechanistic elucidation and clinical translation. This review synthesizes advances in data-driven approaches to parsing ASD heterogeneity and centers the discussion on three complementary strata: neural, behavioral, and transdiagnostic subtypes. At the neuroimaging level, studies leveraging features such as functional connectivity and brain structure have consistently identified two core neurosubtypes characterized by increased and decreased neural activity, respectively. These neurosubtypes differ in time-varying dynamics, spatial architecture, and network hierarchy, and they are closely associated with specific symptom dimensions and cognitive functions. At the behavioral level, data-driven methods delineate phenotypes along axes of severity and functional impairment, and further reveal their links to neural circuits. Transdiagnostic investigations indicate that ASD and frequently co-occurring disorders share neurobiological substrates and cognitive endophenotypes. Collectively, these findings argue against a simple one-to-one correspondence between behavioral and neural subtypes; instead, the evidence is more consistent with multi-to-one, one-to-many, or many-to-many mappings that converge on the overall functional impairment. Notwithstanding this progress, major challenges remain, including sample heterogeneity, methodological inconsistency, and the integration of categorical and dimensional models. Future research should prioritize large samples, multi-site collaboration, longitudinal designs, and transdiagnostic frameworks, coupled with reverse validation via intervention response, to build robust evidence for mechanism-informed individualized assessment and intervention in ASD.
The framework used to evaluate the relevance of animal models-construct, face, and predictive validity-is outlined and the behavioural paradigms used to assess core ASD-related domains in rodents are summarized, including social interaction and communication, restricted and repetitive behaviours, and cognitive flexibility.
Pilar Martinez Olondo, A. de Kerchove d'Exaerde· Developmental Medicine & Chi...· 0 citations
FMRI data from 162 ASD and 175 TD adolescents are analyzed to demonstrate statistical associations among altered spatial-functional properties, clinical severity, and transcriptomic profiles related to synaptic signaling, mitochondrial processes, and glial-related functions in ASD, providing a complementary spatial perspective on large-scale functional organization.
Jun Pan, Heng Zhang, Yiran Zhai et al.· Frontiers in Neuroscience· 0 citations
Elucidating the neurobiological basis of neurodevelopmental and psychiatric conditions (NDPCs) remains challenging because brain alterations vary within diagnoses and overlap across them. Whether diverse alterations follow a systematic organization that may reflect shared vulnerabilities remains unknown. Here, we assembled 10,135 individuals with schizophrenia, autism, bipolar, obsessive-compulsive, generalized anxiety, and major depressive disorders, and 11,998 reference participants across six continents through the ENIGMA consortium. Using normative modeling, we quantified individual deviations in cortical thickness, surface area, and subcortical volumes relative to lifespan reference trajectories (5 to 80 years). We show that structural deviations converged along cortical axes reflecting connectome organization, maturation, and cytoarchitectonic diversity. These axes mirrored typical population variation, but their expression differed across diagnoses and partly scaled with symptom severity. Even rare and highly individualized extreme deviations followed this organization, concentrating in densely connected regions. Finally, brain structural deviations overlapped substantially across diagnoses, while differences between them increased toward the association cortex. Together, we provide large-scale evidence that structural deviations across NDPCs are systematically constrained by the brain's intrinsic architecture. This shared organization provides a framework for reconciling individual variability with transdiagnostic similarities and motivates an integrative, systems-level understanding of mental health.
M. Hettwer, A. Saberi, G. Shafiei et al.· medRxiv· 0 citations
Abstract Background ADHD is a neurodevelopmental disorder characterized by inattention, hyperactivity, and impulsivity, often persisting into adulthood. Despite growing recognition, adult ADHD remains under-studied, and its developmental trajectory relative to childhood ADHD is poorly defined. Understanding age-dependent changes in behavior, neurochemistry, and treatment response is critical for refining diagnosis and therapy. The DAT Val559-KI mouse model carries a human-relevant dopamine transporter mutation and reproduces core ADHD features, providing a translational platform for longitudinal investigation of these questions. Aims & Objectives Characterize developmental trajectories of ADHD-like behaviors (inattention, hyperactivity, impulsivity) from childhood to adulthood. Assess age-dependent treatment responses to methylphenidate, identifying efficacy and tolerability across stages. Map neurochemical changes in dopaminergic and noradrenergic systems underlying behavioral and treatment outcomes. Method DAT Val559-KI mice will be studied longitudinally across developmental stages. Locomotor sensitization assays will determine the optimal clinically translated dose of methylphenidate, which will then be applied in subsequent behavioral and molecular experiments. ADHD-relevant behaviors will be quantified using standardized paradigms assessing attention, impulsivity, and activity. Neurochemical analyses will include in vivo electrophysiology, immunohistochemistry, and molecular profiling to evaluate dopaminergic and noradrenergic signaling changes over time. Results We expect to identify age-specific patterns in ADHD-like behaviors and comorbid traits, distinguishing adult from childhood profiles. Methylphenidate efficacy and side-effect profiles are predicted to vary across developmental stages, providing insight into age-tailored therapeutic strategies. Neurochemical analyses are anticipated to reveal dynamic changes in dopamine and norepinephrine signaling that correlate with behavioral outcomes and treatment responses. Discussion & Conclusions This study integrates longitudinal behavioral, pharmacological, and neurochemical analyses in a humanized ADHD mouse model, addressing key gaps in adult ADHD research. Findings will clarify the developmental progression of core symptoms, inform age-specific treatment strategies, and provide mechanistic insight into dopaminergic and noradrenergic contributions to ADHD. Ultimately, this work supports refinement of diagnostic criteria and the development of tailored interventions across the lifespan.
R. J. Custodio, E. Wascher, S. Getzmann· International Journal of Neu...· 0 citations
Abstract Background Attention-deficit/hyperactivity disorder (ADHD) manifests differently across the lifespan, yet the neurobiological mechanisms driving these changes remain inadequately understood. Aims & Objectives This meta-analysis aims to explore age-related alterations in FC in ADHD and examine the associations with transcriptomic and neurotransmitter signatures. We aim to characterize how these alterations are influenced by developmental stages and their relationship with neurochemical and molecular factors. Method Following PRISMA guidelines, we conducted a seed-based meta-analysis comparing ADHD patients (n = 4,316) and healthy controls (n = 8,709) across 43 studies. Age-stratified analyses (children, adolescents, adults) were performed to examine FC alterations within major cortical and subcortical networks. Meta-regressions were used to investigate age-related effects. Molecular associations were assessed through transcriptomic data and neurotransmitter receptor/transporter maps from publicly available databases. Results A developmentally differentiated pattern of FC alterations was observed, with the most pronounced abnormalities in childhood, partially reversing in adulthood. Within the default mode network (DMN), connectivity with the insula reversed with age, from hypoconnectivity in children to hyperconnectivity in adults. Subgroup analyses of stimulant-naïve datasets confirmed the robustness of these findings. At the molecular level, FC alterations in the sbocortical network (SCN) and DMN were spatially associated with transcriptomic pathways related to synaptic signaling, while children exhibited specific enrichment of neurodevelopmental pathways, and SCN connectivity was linked to stimulus-response-related pathways. Neurotransmitter associations were network- and age-dependent, with dopaminergic and serotonergic markers linked to cortical network changes, and noradrenergic transporter density associated with SCN dysconnectivity in children. Discussion & Conclusions We demonstrates that ADHD is characterized by developmentally FC alterations. We identify a key reversal in DMN-VAN connectivity between child and adult patients, supporting models of delayed maturation and compensatory reorganization. Crucially, the medication-naïve subgroup exhibited more extensive DMN dysconnectivity, suggesting that pharmacological treatment may partially mask intrinsic network deficits. By integrating FC with transcriptomic and neurochemical evidence, we further reveal that these network-level abnormalities are associated with distinct molecular and neuromodulatory mechanisms that vary across networks and developmental stages. Together, these findings advance a multi-system framework for understanding ADHD from childhood to adulthood, bridging macro-scale network dysfunction with meso-scale biological substrates, and offering novel insights for intervention targets.
H. Li, X. Chen, F. Li· International Journal of Neu...· 0 citations
Results indicate that multi-omics integration, in addition to explaining the molecular architecture of MDD, also characterizes patient subgroups with pathophysiological mechanisms, dimensions of symptoms, and disease treatment, which demonstrates that there is a shift in psychiatry toward a more mechanistic approach.
Elham Amjad, B. Sokouti· OBM Neurobiology· 0 citations
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