Sci Rep. 2026 Apr 3. doi: 10.1038/s41598-026-42120-y. Online ahead of print.

Qualitative EEG abnormalities are common in Autism Spectrum Disorder (ASD) and hypothesized to reflect disrupted excitation/inhibition (E/I) balance. To test this, we recently introduced a functional measure of network-level E/I ratio (fE/I). Here, we applied fE/I and other EEG measures to alpha oscillations from source-reconstructed data in the EU-AIMS dataset (267 ASD, 209 controls). We analyzed these measures alongside qualitative EEG abnormalities ranging from slowing of activity to epileptiform patterns, aiming to replicate the findings from the SPACE-BAMBI study. Contrary to our previous report, we did not observe increased fE/I variability in ASD compared to controls. EEG abnormalities were rare in adults and could not be statistically assessed. ASD children-adolescents with EEG abnormalities exhibited lower relative alpha power and fE/I compared to those without. However, EEG-abnormality scoring did not stratify the behavioral heterogeneity of ASD using clinical measures. Surprisingly, several controls also exhibited qualitative EEG abnormalities with a strikingly similar anatomical distribution of reduced fE/I, reflecting inhibition-dominated network dynamics in sensory processing regions. The robustness of this association between EEG abnormalities and reduced fE/I was further supported by re-analysis of the SPACE-BAMBI study in source space. Stratification by the presence of EEG abnormalities and their effects on network activity may help understand neurodevelopmental physiological heterogeneity and the difficulties in implementing E/I targeting treatments in unselected cohorts.

PMID:41932958 | DOI:10.1038/s41598-026-42120-y

Transl Psychiatry. 2026 Mar 24;16(1):201. doi: 10.1038/s41398-026-03932-8.

ABSTRACT

Phelan-McDermid syndrome (PMS) is a relatively frequent cause of syndromic intellectual disability (ID) and autism spectrum disorder (ASD). It is typically caused by genetic alterations in the 22q13 chromosomal region, most often involving heterozygous deletions or mutations in the SHANK3 gene. More than half of affected individuals exhibit functional impairments in speech, cognition, motor skills, and behavior. Despite multiple ongoing therapeutic programs, objective and scalable liquid biomarkers to support patient stratification and to monitor disease course or treatment response are still lacking. Here, in a pilot study involving 23 individuals with PMS, we identified two biomarkers that are significantly altered compared to a control group and are associated with symptom severity. First, SHANK3 protein was detectable in peripheral blood mononuclear cells (PBMCs) and was markedly reduced in PMS (mean -77% vs. controls), consistent with SHANK3 haploinsufficiency; lower PBMC SHANK3 levels were associated with the presence of developmental regression, supporting its potential utility as a target-engagement/monitoring biomarker rather than a diagnostic screen. Additionally, plasma levels of beta-synuclein, a neuron-specific synaptic protein, were elevated in PMS and positively correlated with the severity of speech impairment. Both biomarkers were successfully back-translated in a Shank3 transgenic mouse model, where beta-synuclein levels were normalized through modulation of the mGlu5 receptor. Together, these results provide initial evidence for SHANK3 in PBMCs and plasma beta-synuclein as complementary liquid biomarkers to aid prognosis and enable objective monitoring of therapeutic response in PMS, warranting validation in larger and pediatric longitudinal cohorts.

PMID:41876457 | PMC:PMC13039877 | DOI:10.1038/s41398-026-03932-8

Scand J Psychol. 2026 Mar 9. doi: 10.1111/sjop.70088. Online ahead of print.

ABSTRACT

Autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and developmental language disorder (DLD) are neurodevelopmental conditions (NDCs) that share etiological factors and frequently co-occur. Despite this, they have rarely been studied together-particularly in relation to functional outcomes. In this study, we investigate the association between the developmental pattern of sustained visual attention in infancy and number of diagnoses, and map the clinical profile of 6-year-old children. A cohort of 6-year-olds, originally recruited in infancy due to elevated (n = 42) or low (n = 7) likelihood of ASD, were assessed for sustained visual attention, diagnostic outcomes, general adaptive functioning, intellectual abilities, and language skills. Participants were grouped based on the number of NDC diagnoses (ASD, ADHD, DLD, and/or Subthreshold ASD) they received at follow-up. We could not find statistical support for an association between sustained visual attention and number of diagnoses. Findings revealed no significant differences in adaptive functioning, intellectual abilities, or language skills between children with no diagnosis (n = 24) and those with a single diagnosis (n = 15). However, children with two or more diagnoses (n = 10) scored significantly lower in general adaptive functioning, intellectual ability, language production, and verbal comprehension compared to those with only one or no diagnosis. The results indicate that compared to children with only one diagnosis or no diagnosis, children with two or more diagnoses scored lower on several key functional domains, emphasizing the need to prioritize children with multiple diagnoses or confirmed functional impairment in clinical settings. Moreover, the findings indicate that a single diagnosis in preschool-aged children should not be a stand-alone outcome measure in sibling studies, if the goal is to identify early processes that predict meaningful differences in everyday functioning.

PMID:41802979 | DOI:10.1111/sjop.70088

J Autism Dev Disord. 2026 Jan 28. doi: 10.1007/s10803-025-07165-4. Online ahead of print.

ABSTRACT

PURPOSE: The aim of the study is to examine (i) if young children with a family history of autism and/or ADHD differ on executive functions and deferred gratification in comparison to peers with no family history of autism or ADHD, (ii) the specificity of these domains in relation to early-life autistic and ADHD symptoms and adaptive functioning, and (iii) if deferred gratification and strong EF skills may function as protective factors in the association between symptoms and adaptive behaviour.

METHODS: A total of 77 infant siblings at 3 years of age with a family history of autism only, autism and co-occurring ADHD, or no family history of these conditions (FH-TL) were assessed on behavioural lab-tasks (EF and deferred gratification), parent-rated adaptive behaviour using Vineland, and clinician ratings using ADOS-2 (autistic symptoms) and ADHD DSM-5 symptom rating scale (ADHD RS).

RESULTS: Group comparisons showed that FH-autism and FH-autism + ADHD groups received lower scores on common EF, but not on deferred gratification in comparison to the FH-TL group. Lower levels of deferred gratification related to autistic symptoms, while lower level on EF was specific to ADHD symptoms. Finally, deferred gratification moderated the association between autistic symptoms and adaptive behaviour, in that stronger ability to defer gratification attenuated the association between autistic symptoms and adaptive functions.

CONCLUSIONS: These results are in line with the idea that strong ability to inhibit and defer gratification may act as a protective factor for children with a family history of autism and/or ADHD pointing to affective aspects of EF as particularly important.

PMID:41604129 | DOI:10.1007/s10803-025-07165-4

Front Neurosci. 2025 Apr 30;19:1488709. doi: 10.3389/fnins.2025.1488709. eCollection 2025.

ABSTRACT

Manual scoring of longitudinal electroencephalographical (EEG) data is a slow and time-consuming process. Current advances in the application of machine-learning and artificial intelligence to EEG data are moving fast; however, there is still a need for expert raters to validate scoring of EEG data. We hypothesized that power-frequency profiles are determining the state and ‘set the framework’ for communication between neurons. Based on these assumptions, a scoring method with a set frequency profile for each vigilance state, both in sleep and awake, was developed and validated. We defined seven states of the functional brain with unique profiles in terms of frequency-power spectra, coherence, phase-amplitude coupling, α exponent, functional excitation-inhibition balance (fE/I), and aperiodic exponent. The new method requires a manual check of wake-sleep transitions and is therefore considered semi-automatic. This semi-automatic approach showed similar α exponent and fE/I when compared to traces scored manually. The new method was faster than manual scoring, and the advanced outcomes of each state were stable across datasets and epoch length. When applying the new method to the neurexin-1α (Nrxn1α) gene deficient mouse, a model of synaptic dysfunction relevant to autism spectrum disorders, several genotype differences in the 24-h distribution of vigilance states were detected. Most prominent was the decrease in slow-wave sleep when comparing wild-type mice to Nrxn1α-deficient mice. This new methodology puts forward an optimized and validated EEG analysis pipeline for the identification of translational electrophysiological biomarkers for brain disorders that are related to sleep architecture and E/I balance.

PMID:40370661 | PMC:PMC12075235 | DOI:10.3389/fnins.2025.1488709

J Child Psychol Psychiatry. 2025 Aug;66(8):1182-1196. doi: 10.1111/jcpp.14143. Epub 2025 Mar 4.

ABSTRACT

BACKGROUND: Infants vary significantly in the way they process and respond to sensory stimuli, and altered sensory processing has been reported among infants later diagnosed with autism. Previous work with adolescents and adults suggests that variability in sensory processing may have a strong genetic basis. Yet, little is known about the etiological factors influencing sensory differences in infancy, when brain circuits supporting social and non-social cognition are sculpted and learning about the world via sensory input largely occurs in interaction with caregivers.

METHODS: We analysed data from a community sample of monozygotic (MZ) and dizygotic (DZ) 5-month-old same-sex twins (n = 285 pairs, n = 158 MZ pairs, n = 150 male pairs) from the BabyTwins Study in Sweden (BATSS) using exploratory factor analysis, generalised estimating equations and multivariate twin models to delineate the phenotypic and etiological structure of individual variability across different sensory processing dimensions, as measured by the Infant/Toddler Sensory Profile. Developmental links to later autistic traits were also assessed, as measured by total scores from the Quantitative Checklist for Autism in Toddlers at 36 months.

RESULTS: Results suggested separability between sensory processing dimensions (i.e. sensation seeking, sensation avoiding, sensory sensitivity and low registration) at a phenotypic and etiological level, with significant contributions from additive genetics and family environment that were unique to each sensory dimension and significant but smaller contributions from shared influences. Sensory domains also showed etiological separability, with unique genetic influences to each domain, while contributions from shared environment were in part shared across domains. A higher incidence of tactile-related behaviours and behaviours associated with sensory sensitivity, sensation avoiding, and low registration were significantly associated with higher levels of autistic traits in toddlerhood.

CONCLUSIONS: This study provides a map of the phenotypic and etiological structure of sensory processing in infancy, which will be informative for studies of both typical and atypical development.

PMID:40035145 | PMC:PMC12267685 | DOI:10.1111/jcpp.14143

Nat Ment Health. 2025;3(1):31-45. doi: 10.1038/s44220-024-00349-4. Epub 2025 Jan 2.

ABSTRACT

Atypical face processing is commonly reported in autism. Its neural correlates have been explored extensively across single neuroimaging modalities within key regions of the face processing network, such as the fusiform gyrus (FFG). Nonetheless, it is poorly understood how variation in brain anatomy and function jointly impacts face processing and social functioning. Here we leveraged a large multimodal sample to study the cross-modal signature of face processing within the FFG across four imaging modalities (structural magnetic resonance imaging (MRI), resting-state functional magnetic resonance imaging, task-functional magnetic resonance imaging and electroencephalography) in 204 autistic and nonautistic individuals aged 7-30 years (case-control design). We combined two methodological innovations-normative modeling and linked independent component analysis-to integrate individual-level deviations across modalities and assessed how multimodal components differentiated groups and informed social functioning in autism. Groups differed significantly in a multimodal component driven by bilateral resting-state functional MRI, bilateral structure, right task-functional MRI and left electroencephalography loadings in face-selective and retinotopic FFG. Multimodal components outperformed unimodal ones in differentiating groups. In autistic individuals, multimodal components were associated with cognitive and clinical features linked to social, but not nonsocial, functioning. These findings underscore the importance of elucidating multimodal neural associations of social functioning in autism, offering potential for the identification of mechanistic and prognostic biomarkers.

PMID:39802935 | PMC:PMC11717707 | DOI:10.1038/s44220-024-00349-4

Mol Psychiatry. 2025 Apr;30(4):1627-1638. doi: 10.1038/s41380-024-02878-x. Epub 2024 Dec 27.

ABSTRACT

Psychiatric disorders are highly comorbid, heritable, and genetically correlated [1-4]. The primary objective of cross-disorder psychiatric genetics research is to identify and characterize both the shared genetic factors that contribute to convergent disease etiologies and the unique genetic factors that distinguish between disorders [4, 5]. This information can illuminate the biological mechanisms underlying comorbid presentations of psychopathology, improve nosology and prediction of illness risk and trajectories, and aid the development of more effective and targeted interventions. In this review we discuss how estimates of comorbidity and identification of shared genetic loci between disorders can be influenced by how disorders are measured (phenotypic assessment) and the inclusion or exclusion criteria in individual genetic studies (sample ascertainment). Specifically, the depth of measurement, source of diagnosis, and time frame of disease trajectory have major implications for the clinical validity of the assessed phenotypes. Further, biases introduced in the ascertainment of both cases and controls can inflate or reduce estimates of genetic correlations. The impact of these design choices may have important implications for large meta-analyses of cohorts from diverse populations that use different forms of assessment and inclusion criteria, and subsequent cross-disorder analyses thereof. We review how assessment and ascertainment affect genetic findings in both univariate and multivariate analyses and conclude with recommendations for addressing them in future research.

PMID:39730880 | PMC:PMC11919726 | DOI:10.1038/s41380-024-02878-x