Background Autism is hypothesized to represent a disorder of brain connectivity, yet patterns of atypical functional connectivity show marked heterogeneity across individuals. Methods We used a large multi-site dataset comprised of a heterogeneous population of individuals with autism and typically developing individuals to compare a number of resting-state functional connectivity features of autism. These features were also tested in a single site sample that utilized a high-temporal resolution, long-duration resting-state acquisition technique. Results No one method of analysis provided reproducible results across research sites, combined samples, and the high-resolution dataset. Distinct categories of functional connectivity features that differed in autism such as homotopic, default network, salience network, long-range connections, and corticostriatal connectivity, did not align with differences in clinical and behavioral traits in individuals with autism. One method, lag-based functional connectivity, was not correlated to other methods in describing patterns of resting-state functional connectivity and their relationship to autism traits. Conclusion Overall, functional connectivity features predictive of autism demonstrated limited generalizability across sites, with consistent results only for large samples. Different types of functional connectivity features do not consistently predict different symptoms of autism. Rather, specific features that predict autism symptoms are distributed across feature types. Electronic supplementary material The online version of this article (10.1186/s13229-019-0273-5) contains supplementary material, which is available to authorized users.

The complexity and heterogeneity of neuroimaging findings in individuals with autism spectrum disorder has suggested that many of the underlying alterations are subtle and involve many brain regions and networks. The ability to account for multivariate brain features and identify neuroimaging measures that can be used to characterize individual variation have thus become increasingly important for interpreting and understanding the neurobiological mechanisms of autism. In the present study, we utilize the Mahalanobis distance, a multidimensional counterpart of the Euclidean distance, as an informative index to characterize individual brain variation and deviation in autism. Longitudinal diffusion tensor imaging data from 149 participants (92 diagnosed with autism spectrum disorder and 57 typically developing controls) between 3.1 and 36.83 years of age were acquired over a roughly 10-year period and used to construct the Mahalanobis distance from regional measures of white matter microstructure. Mahalanobis distances were significantly greater and more variable in the autistic individuals as compared to control participants, demonstrating increased atypicalities and variation in the group of individuals diagnosed with autism spectrum disorder. Distributions of multivariate measures were also found to provide greater discrimination and more sensitive delineation between autistic and typically developing individuals than conventional univariate measures, while also being significantly associated with observed traits of the autism group. These results help substantiate autism as a truly heterogeneous neurodevelopmental disorder, while also suggesting that collectively considering neuroimaging measures from multiple brain regions provides improved insight into the diversity of brain measures in autism that is not observed when considering the same regions separately. Distinguishing multidimensional brain relationships may thus be informative for identifying neuroimaging-based phenotypes, as well as help elucidate underlying neural mechanisms of brain variation in autism spectrum disorders.

Key Points Question Do individuals with autism show atypical duration of brain functional connections? Findings In this cohort study of 52 individuals with autism and 38 typically developing participants and a replication study of 1402 participants in a brain imaging database, increased durations of functional connections in autism were found in both distributed networks and individual brain regions, which were associated with metrics of disease severity. Meaning Persistence of brain connectivity in autism may limit the ability to rapidly shift from one brain state to another and contribute to the pathophysiology of autism.

Microstructure of the thalamus, a key sensory and motor brain area, appears to develop differently in individuals with autism spectrum disorder (ASD). Microstructure is important because it informs us of the density and organization of different brain tissues. During childhood, thalamic microstructure was distinct in the ASD group compared to the typically developing group. However, these group differences appeared to narrow with age, suggesting that the thalamus continues to dynamically change in ASD into adulthood.

Intelligence (IQ) scores are used in educational and vocational planning for individuals with autism spectrum disorder (ASD) yet little is known about the stability of IQ throughout development. We examined longitudinal age-related IQ stability in 119 individuals with ASD (3–36 years of age at first visit) and 128 typically developing controls. Intelligence measures were collected over a 20-year period. In ASD, Full Scale (FSIQ) and Verbal (VIQ) Intelligence started lower in childhood and increased at a greater rate with age relative to the control group. By early adulthood, VIQ and working memory stabilized, whereas nonverbal and perceptual scores continued to change. Our results suggest that in individuals with ASD, IQ estimates may be dynamic in childhood and young adulthood.

Purpose of review Impairments in social interaction/communication become apparent after 12 months of age in children who develop Autism spectrum disorder (ASD). Studies of baby siblings of children with ASD provide the means to detect changes in the brain that are present before behavioral symptoms appear. In this review, advances from brain imaging studies of infant siblings over the past 18 months are highlighted. Recent findings During the first 2 months of life, functional differences in social brain regions and microstructural differences in dorsal language tracks are found in some high-risk baby siblings. At 4–6 months of age, differences in subcortical and cerebellum volumes and atypical cortical responses to social stimuli are evident. At 6 months, extra-axial cerebrospinal fluid is increased, and at 8 months there is evidence of cortical hyper-reactivity. Patterns of functional connectivity are distinct in infant siblings and suggest dysfunctional activation and integration of information across the cortex and neural networks underlying social behaviors. Summary Further replication in very large independent samples is needed to verify the majority of the findings discussed and understand how they are related within individual infants. Much more research is needed before translation to clinical practice.

A test-retest study of FreeSurfer derived cortical thickness, cortical surface area, and cortical volume, as well as quantitative R1 relaxometry assessed on the midpoint of the cortex, was performed on a cohort of pediatric subjects (6–12 years old) scanned without sedation using SNARE-MPnRAGE ( s elf na vigated re trospective motion corrected m agnetization p repared with n r apid g radient e choes) imaging. Reliability was assessed with coefficients of variation (CoVs) and intraclass correlation coefficients (ICCs) and statistical tests were used to determine differences with and without SNARE motion correction. Comparison of the test-retest measures of SNARE-MPnRAGE with prospectively motion corrected PROMO MPRAGE were also performed. When SNARE motion correction was used all parameters had statistically significant improvements and demonstrated high reliability. Reliability varied depending on parameter, region, and measurement type (vertex or region of interest). For mean thickness/surface area/volume/mean R1 across the regions of FreeSurfer’s DK Atlas, the mean CoVs (% x100) were (1.2/1.6/1.9/0.9) and the mean ICCs were (0.88/0.96/0.94/0.83). When assessed on a per-vertex basis, the CoVs and ICCs for thickness/R1 had mean values of (2.9/1.9) and (0.82/0.68) across the regions of the DK Atlas. Retrospectively motion corrected MPnRAGE had significantly lower CoVs and higher ICCs for the morphological measures than PROMO MPRAGE. Motion correction effectively removed motion related biases in nearly all regions for R1 and morphometric measures.

As a medical specialty, genetic counseling (GC) espouses cultural sensitivity, a patientcentered approach, and an eye for the individual, familial, and community-wide implications of genetics and genomics in medicine. Within the past decades, the field of GC has recognized and attempted to address a need for the greater diversity of providers and practice settings that will help to address health inequities across underrepresented communities (Channaoui et al., 2020). Accreditation for GC training programs mandates equipping students with multicultural sensitivity and knowledge on health disparities. Currently however, there are limited published data about how GC programs are accomplishing these aims for Native American individuals and communities. Furthermore, there are limited published data on the unique needs and perspectives of Native Americans who may seek GC services. This disconnect may pose barriers for genetic counselors who aim to provide respectful and relevant care to Native American patients. Education of GC students is one important way to set the tone for a lifetime of practice and to inspire awareness and action toward alleviating disparities. Thus, we surveyed GC training programs in North America to investigate how they are working to (a) address disparities in Native American professional representation and student enrollment, (b) deliver culturally relevant curricula and clinical opportunities that serve the needs of Native Americans, and (c) positively engage Native American communities in North America. We found that reported recruitment efforts, curricula content, clinical opportunities, and community engagement efforts to address the needs of Native American are limited across GC training programs surveyed. By bringing awareness to current methods, success factors, and barriers in this space, we hope to open the door for meaningful partnerships between leaders of Native American communities and GC training programs in the pursuit of greater equity.