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Background: Autistic-like traits (ALT) are prevalent across the general population and might be linked to some facets of a broader autism spectrum disorder (ASD) phenotype. Recent studies suggest an association of these traits with both genetic and brain structural markers in non-autistic individuals, showing similar spatial location of findings observed in ASD and thus suggesting a potential neurobiological continuum., Methods: In this study, we first tested an association of ALTs (assessed with the AQ questionnaire) with cortical complexity, a cortical surface marker of early neurodevelopment, and then the association with disrupted functional connectivity. We analysed structural T1-weighted and resting-state functional MRI scans in 250 psychiatrically healthy individuals without a history of early developmental disorders, in a first step using the CAT12 toolbox for cortical complexity analysis and in a second step we used regional cortical complexity findings to apply the CONN toolbox for seed-based functional connectivity analysis., Results: Our findings show a significant negative correlation of both AQ total and AQ attention switching subscores with left superior temporal sulcus (STS) cortical folding complexity, with the former being significantly correlated with STS to left lateral occipital cortex connectivity, while the latter showed significant positive correlation of STS to left inferior/middle frontal gyrus connectivity (n = 233; all p < 0.05, FWE cluster-level corrected). Additional analyses also revealed a significant correlation of AQ attention to detail subscores with STS to left lateral occipital cortex connectivity., Limitations: Phenotyping might affect association results (e.g. choice of inventories); in addition, our study was limited to subclinical expressions of autistic-like traits., Conclusions: Our findings provide further evidence for biological correlates of ALT even in the absence of clinical ASD, while establishing a link between structural variation of early developmental origin and functional connectivity., (© 2024. The Author(s).)

Background: Although autism spectrum disorder (ASD) is a common developmental disorder, our knowledge about a behavioral and neurobiological female phenotype is still scarce. As the conceptualization and understanding of ASD are mainly based on the investigation of male individuals, females with ASD may not be adequately identified by routine clinical diagnostics. The present machine learning approach aimed to identify diagnostic information from the Autism Diagnostic Observation Schedule (ADOS) that discriminates best between ASD and non-ASD in females and males., Methods: Random forests (RF) were used to discover patterns of symptoms in diagnostic data from the ADOS (modules 3 and 4) in 1057 participants with ASD (18.1% female) and 1230 participants with non-ASD (17.9% % female). Predictive performances of reduced feature models were explored and compared between females and males without intellectual disabilities., Results: Reduced feature models relied on considerably fewer features from the ADOS in females compared to males, while still yielding similar classification performance (e.g., sensitivity, specificity)., Limitations: As in previous studies, the current sample of females with ASD is smaller than the male sample and thus, females may still be underrepresented, limiting the statistical power to detect small to moderate effects., Conclusion: Our results do not suggest the need for new or altered diagnostic algorithms for females with ASD. Although we identified some phenotypic differences between females and males, the existing diagnostic tools seem to sufficiently capture the core autistic features in both groups., (© 2022. The Author(s).)

Background: Early identification of autism spectrum disorders (ASD) is a prerequisite for access to early interventions. Although parents often note developmental atypicalities during the first 2 years of life, many children with ASD are not diagnosed until school age. For parents, the long period between first parental concerns and diagnosis is often frustrating and accompanied by uncertainty and worry., Methods: This study retrospectively explored the trajectories of children with a confirmed ASD diagnosis during the diagnostic process, from first parental concerns about their child's development until the definite diagnosis. A survey concerning the diagnostic process was distributed to parents or legal guardians of children with ASD from three specialized ASD outpatient clinics in Germany., Results: The response rate was 36.9%, and the final sample consisted of carers of 207 affected children (83.6% male, mean age 12.9 years). The children had been diagnosed with childhood autism (55.6%), Asperger syndrome (24.2%), or atypical autism (20.3%). On average, parents had first concerns when their child was 23.4 months old, and an ASD diagnosis was established at a mean age of 78.5 months. Children with atypical autism or Asperger syndrome were diagnosed significantly later (83.9 and 98.1 months, respectively) than children with childhood autism (68.1 months). Children with an IQ < 85 were diagnosed much earlier than those with an IQ ≥ 85. On average, parents visited 3.4 different health professionals (SD = 2.4, range 1-20, median: 3.0) until their child received a definite ASD diagnosis. Overall, 38.5% of carers were satisfied with the diagnostic process., Conclusions: In this sample of children with ASD in Germany, the time to diagnosis was higher than in the majority of other comparable studies. These results flag the need for improved forms of service provision and delivery for suspected cases of ASD in Germany., Competing Interests: The authors declare that they have no competing interests.

Background: Complementary and Alternative Medicine (CAM) is widely used both in the general population and for the treatment of somatic and psychiatric disorders. Studies on CAM use among patients with autism spectrum disorder (ASD) have so far only focused on children and adolescents. The aim of this study was to investigate patterns of CAM use among adults with ASD., Methods: A questionnaire survey concerning current and lifetime use of CAM was distributed to adults with ASD between November 2015 and June 2016. Participants diagnosed by experienced clinicians using the current diagnostic gold standard were recruited from four ASD outpatient clinics in Germany. Questionnaire data was then linked to supplementary clinical data., Results: The final sample consisted of 192 adults (response: 26.8%) with a mean age of 31.5 years (80% male; diagnoses: Asperger's syndrome (58%), childhood autism (27%), atypical autism (12%)). 45% of the respondents stated that they were currently using or had used at least one CAM modality in their life. Among the participants with lifetime CAM use, almost half had used two or more different types of CAM. Alternative medical systems (e.g. homeopathy, acupuncture) were most frequently used, followed by mind-body interventions (e.g. yoga, biofeedback, animal assisted therapy). Overall, 20% of respondents stated that they would like to try at least one listed CAM modality in the future., Conclusions: This is the first study on CAM use in adults with ASD, demonstrating considerable CAM use in this population. Given the popularity of CAM, patients should be informed about the effectiveness and potentially dangerous side effects of CAM treatments, as evidence for the majority of CAM methods in ASD is still limited.

Background: Autism Spectrum Disorder (ASD) is a severe, lifelong neurodevelopmental disorder with early onset that places a heavy burden on affected individuals and their families. Due to the need for highly specialized health, educational and vocational services, ASD is a cost-intensive disorder, and strain on health care systems increases with increasing age of the affected individual., Methods: The ASD-Net will study Germany's largest cohort of patients with ASD over the lifespan. By combining methodological expertise from all levels of clinical research, the ASD-Net will follow a translational approach necessary to identify neurobiological pathways of different phenotypes and their appropriate identification and treatment. The work of the ASD-Net will be organized into three clusters concentrating on diagnostics, therapy and health economics. In the diagnostic cluster, data from a large, well-characterized sample (N = 2568) will be analyzed to improve the efficiency of diagnostic procedures. Pattern classification methods (machine learning) will be used to identify algorithms for screening purposes. In a second step, the developed algorithm will be tested in an independent sample. In the therapy cluster, we will unravel how an ASD-specific social skills training with concomitant oxytocin administration can modulate behavior through neurobiological pathways. For the first time, we will characterize long-term effects of a social skills training combined with oxytocin treatment on behavioral and neurobiological phenotypes. Also acute effects of oxytocin will be investigated to delineate general and specific effects of additional oxytocin treatment in order to develop biologically plausible models for symptoms and successful therapeutic interventions in ASD. Finally, in the health economics cluster, we will assess service utilization and ASD-related costs in order to identify potential needs and cost savings specifically tailored to Germany. The ASD-Net has been established as part of the German Research Network for Mental Disorders, funded by the BMBF (German Federal Ministry of Education and Research)., Discussion: The highly integrated structure of the ASD-Net guarantees sustained collaboration of clinicians and researchers to alleviate individual distress, harm, and social disability of patients with ASD and reduce costs to the German health care system., Trial Registration: Both clinical trials of the ASD-Net are registered in the German Clinical Trials Register: DRKS00008952 (registered on August 4, 2015) and DRKS00010053 (registered on April 8, 2016).