Atypical functional connectivity between the amygdala and visual, salience regions in infants with genetic liability for autism

The amygdala undergoes a period of overgrowth in the first year of life, resulting in enlarged volume by 12 months in infants later diagnosed with ASD. The overgrowth of the amygdala may have functional consequences during infancy. We investigated whether amygdala connectivity differs in 12-month-olds at high likelihood (HL) for ASD (defined by having an older sibling with autism), compared to those at low likelihood (LL). We examined seed-based connectivity of left and right amygdalae, hypothesizing that the HL and LL groups would differ in amygdala connectivity, especially with the visual cortex, based on our prior reports demonstrating that components of visual circuitry develop atypically and are linked to genetic liability for autism. We found that HL infants exhibited weaker connectivity between the right amygdala and the left visual cortex, as well as between the left amygdala and the right anterior cingulate, with evidence that these patterns occur in distinct subgroups of the HL sample. Amygdala connectivity strength with the visual cortex was related to motor and communication abilities among HL infants. Findings indicate that aberrant functional connectivity between the amygdala and visual regions is apparent in infants with genetic liability for ASD and may have implications for early differences in adaptive behaviors.

Neurobehavioral outcomes of neonatal asymptomatic congenital cytomegalovirus infection at 12-months

BACKGROUND

Congenital cytomegalovirus (cCMV) is the most common congenital viral infection in the United States. Symptomatic infections can cause severe hearing loss and neurological disability, although ~ 90% of cCMV infections are asymptomatic at birth. Despite its prevalence, the long-term neurobehavioral risks of asymptomatic cCMV infections are not fully understood. The objective of this work was to evaluate for potential long-term neurobehavioral sequelae in infants with asymptomatic cCMV.

METHODS

Infants with cCMV were identified from a universal newborn cCMV screening study in a metropolitan area in the midwestern United States. Asymptomatic infants with cCMV were enrolled in a longitudinal neurodevelopmental study (N = 29). Age- and sex-matched healthy control infants (N = 193) were identified from the Baby Connectome Project (BCP), a longitudinal study of brain and behavioral development. The BCP sample supplemented an additional group of healthy control infants (N = 30), recruited from the same participant registry as the BCP specifically for comparison with infants with asymptomatic cCMV. Neurobehavioral assessments and parent questionnaires, including the Mullen Scales of Early Learning, the Repetitive Behavior Scales for Early Childhood (RBS-EC), and the Infant Toddler Social Emotional Assessment (ITSEA) were administered at 12 months of age. Neurobehavioral scores were compared between infants with asymptomatic cCMV and all identified healthy control infants.

RESULTS

Infants with asymptomatic cCMV performed equivalently compared to healthy control infants on the neurobehavioral measures tested at 12 months of age.

CONCLUSIONS

These results indicate that at 12 months of age, infants with asymptomatic cCMV are not statistically different from controls in a number of neurobehavioral domains. Although follow-up is ongoing, these observations provide reassurance about neurobehavioral outcomes for infants with asymptomatic cCMV and inform the ongoing discussion around universal screening. Additional follow-up will be necessary to understand the longer-term outcomes of these children.

Neural correlates of novelty-evoked distress in 4-month-old infants: A synthetic cohort study

BACKGROUND

Observational assessments of infant temperament have provided unparalleled insight into prediction of risk for social anxiety. Yet, it is challenging to administer and score these assessments alongside high-quality infant neuroimaging data. The current study aims to identify infant resting state functional connectivity (rsFC) associated with both parent-report and observed behavioral estimates of infant novelty-evoked distress.

METHODS

Using data from the Origins of Infant Temperament (OIT) study which includes deep phenotyping of infant temperament, we identified parent-report measures that were associated with observed novelty-evoked distress. These parent-report measures were then summarized into a composite score used for imaging analysis. Our infant MRI sample was a "synthetic cohort", harmonizing data from two fMRI studies of 4-month-old infants (OIT and Baby Connectome Project [BCP]; n=101) both of which included parent-reported temperament. Brain-behavior associations were evaluated using "enrichment," a statistical approach that quantifies the clustering of brain-behavior associations within network pairs.

RESULTS

Results demonstrated that parent-report composites of novelty-evoked distress were significantly associated with three network pairs: Dorsal Attention-Salience/Ventral Attention, Dorsal Attention-Default, and Dorsal Attention-Control. These network pairs demonstrated negative associations with novelty-evoked distress-indicating that less connectivity between these network pairs was associated with greater novelty-evoked distress. Additional analyses demonstrated that Dorsal Attention -Control network connectivity was associated with observed novelty-evoked distress in the OIT sample (n=38).

CONCLUSION

Overall, this work is broadly consistent with existing work and implicates dorsal attention network connectivity in novelty-evoked distress. This study provides novel data on the neural basis of infant novelty-evoked distress.

Multi-level fMRI analysis applied to hemispheric specialization in the language network, functional areas, and their behavioral correlations in the ABCD sample

Prior research suggests that the organization of the language network in the brain is left-dominant and becomes more lateralized with age and increasing language skill. The age at which specific components of the language network become adult-like varies depending on the abilities they subserve. So far, a large, developmental study has not included a language task paradigm, so we introduce a method to study resting-state laterality in the Adolescent Brain Cognitive Development (ABCD) study. Our approach mixes source timeseries between left and right homotopes of the (1) inferior frontal and (2) middle temporal gyri and (3) a region we term "Wernicke's area" near the supramarginal gyrus. Our large subset sample size of ABCD (n = 6153) allows improved reliability and validity compared to previous, smaller studies of brain-behavior associations. We show that behavioral metrics from the NIH Youth Toolbox and other resources are differentially related to tasks with a larger linguistic component over ones with less (e.g., executive function-dominant tasks). These baseline characteristics of hemispheric specialization in youth are critical for future work determining the correspondence of lateralization with language onset in earlier stages of development.

Infants who develop autism show smaller inventories of deictic and symbolic gestures at 12 months of age

Gestures are an important social communication skill that infants and toddlers use to convey their thoughts, ideas, and intentions. Research suggests that early gesture use has important downstream impacts on developmental processes, such as language learning. However, autistic children are more likely to have challenges in their gestural development. The current study expands upon previous literature on the differences in gesture use between young autistic and non-autistic toddlers by collecting data using a parent-report questionnaire called the MCDI-Words and Gestures at three time points, 12, 18, and 24 months of age. Results (N = 467) showed that high-likelihood infants who later met diagnostic criteria for ASD (n = 73 HL-ASD) have attenuated gesture growth from 12 to 24 months for both deictic gestures and symbolic gestures when compared to high-likelihood infants who later did not meet criteria for ASD (n = 249 HL-Neg) and low-likelihood infants who did not meet criteria for ASD (n = 145 LL-Neg). Other social communicative skills, like play behaviors and imitation, were also found to be impacted in young autistic children when compared to their non-autistic peers. Understanding early differences in social communication growth before a formal autism diagnosis can provide important insights for early intervention.

White matter development and language abilities during infancy in autism spectrum disorder

White matter (WM) fiber tract differences are present in autism spectrum disorder (ASD) and could be important markers of behavior. One of the earliest phenotypic differences in ASD are language atypicalities. Although language has been linked to WM in typical development, no work has evaluated this association in early ASD. Participants came from the Infant Brain Imaging Study and included 321 infant siblings of children with ASD at high likelihood (HL) for developing ASD; 70 HL infants were later diagnosed with ASD (HL-ASD), and 251 HL infants were not diagnosed with ASD (HL-Neg). A control sample of 140 low likelihood infants not diagnosed with ASD (LL-Neg) were also included. Infants contributed expressive language, receptive language, and diffusion tensor imaging data at 6-, 12-, and 24 months. Mixed effects regression models were conducted to evaluate associations between WM and language trajectories. Trajectories of microstructural changes in the right arcuate fasciculus were associated with expressive language development. HL-ASD infants demonstrated a different developmental pattern compared to the HL-Neg and LL-Neg groups, wherein the HL-ASD group exhibited a positive association between WM fractional anisotropy and language whereas HL-Neg and LL-Neg groups showed weak or no association. No other fiber tracts demonstrated significant associations with language. In conclusion, results indicated arcuate fasciculus WM is linked to language in early toddlerhood for autistic toddlers, with the strongest associations emerging around 24 months. To our knowledge, this is the first study to evaluate associations between language and WM development during the pre-symptomatic period in ASD.

Social motivation in infancy is associated with familial recurrence of ASD

Pre-diagnostic deficits in social motivation are hypothesized to contribute to autism spectrum disorder (ASD), a heritable neurodevelopmental condition. We evaluated psychometric properties of a social motivation index (SMI) using parent-report item-level data from 597 participants in a prospective cohort of infant siblings at high and low familial risk for ASD. We tested whether lower SMI scores at 6, 12, and 24 months were associated with a 24-month ASD diagnosis and whether social motivation's course differed relative to familial ASD liability. The SMI displayed good internal consistency and temporal stability. Children diagnosed with ASD displayed lower mean SMI T-scores at all ages and a decrease in mean T-scores across age. Lower group-level 6-month scores corresponded with higher familial ASD liability. Among high-risk infants, strong decline in SMI T-scores was associated with 10-fold odds of diagnosis. Infant social motivation is quantifiable by parental report, differentiates children with versus without later ASD by age 6 months, and tracks with familial ASD liability, consistent with a diagnostic and susceptibility marker of ASD. Early decrements and decline in social motivation indicate increased likelihood of ASD, highlighting social motivation's importance to risk assessment and clarification of the ontogeny of ASD.

Associations between early trajectories of amygdala development and later school-age anxiety in two longitudinal samples

Amygdala function is implicated in the pathogenesis of autism spectrum disorder (ASD) and anxiety. We investigated associations between early trajectories of amygdala growth and anxiety and ASD outcomes at school age in two longitudinal studies: high- and low-familial likelihood for ASD, Infant Brain Imaging Study (IBIS, n = 257) and typically developing (TD) community sample, Early Brain Development Study (EBDS, n = 158). Infants underwent MRI scanning at up to 3 timepoints from neonate to 24 months. Anxiety was assessed at 6-12 years. Linear multilevel modeling tested whether amygdala volume growth was associated with anxiety symptoms at school age. In the IBIS sample, children with higher anxiety showed accelerated amygdala growth from 6 to 24 months. ASD diagnosis and ASD familial likelihood were not significant predictors. In the EBDS sample, amygdala growth from birth to 24 months was associated with anxiety. More anxious children had smaller amygdala volume and slower rates of amygdala growth. We explore reasons for the contrasting results between high-familial likelihood for ASD and TD samples, grounding results in the broader literature of variable associations between early amygdala volume and later anxiety. Results have the potential to identify mechanisms linking early amygdala growth to later anxiety in certain groups.

Endophenotype trait domains for advancing gene discovery in autism spectrum disorder

Autism spectrum disorder (ASD) is associated with a diverse range of etiological processes, including both genetic and non-genetic causes. For a plurality of individuals with ASD, it is likely that the primary causes involve multiple common inherited variants that individually account for only small levels of variation in phenotypic outcomes. This genetic landscape creates a major challenge for detecting small but important pathogenic effects associated with ASD. To address similar challenges, separate fields of medicine have identified endophenotypes, or discrete, quantitative traits that reflect genetic likelihood for a particular clinical condition and leveraged the study of these traits to map polygenic mechanisms and advance more personalized therapeutic strategies for complex diseases. Endophenotypes represent a distinct class of biomarkers useful for understanding genetic contributions to psychiatric and developmental disorders because they are embedded within the causal chain between genotype and clinical phenotype, and they are more proximal to the action of the gene(s) than behavioral traits. Despite their demonstrated power for guiding new understanding of complex genetic structures of clinical conditions, few endophenotypes associated with ASD have been identified and integrated into family genetic studies. In this review, we argue that advancing knowledge of the complex pathogenic processes that contribute to ASD can be accelerated by refocusing attention toward identifying endophenotypic traits reflective of inherited mechanisms. This pivot requires renewed emphasis on study designs with measurement of familial co-variation including infant sibling studies, family trio and quad designs, and analysis of monozygotic and dizygotic twin concordance for select trait dimensions. We also emphasize that clarification of endophenotypic traits necessarily will involve integration of transdiagnostic approaches as candidate traits likely reflect liability for multiple clinical conditions and often are agnostic to diagnostic boundaries. Multiple candidate endophenotypes associated with ASD likelihood are described, and we propose a new focus on the analysis of "endophenotype trait domains" (ETDs), or traits measured across multiple levels (e.g., molecular, cellular, neural system, neuropsychological) along the causal pathway from genes to behavior. To inform our central argument for research efforts toward ETD discovery, we first provide a brief review of the concept of endophenotypes and their application to psychiatry. Next, we highlight key criteria for determining the value of candidate endophenotypes, including unique considerations for the study of ASD. Descriptions of different study designs for assessing endophenotypes in ASD research then are offered, including analysis of how select patterns of results may help prioritize candidate traits in future research. We also present multiple candidate ETDs that collectively cover a breadth of clinical phenomena associated with ASD, including social, language/communication, cognitive control, and sensorimotor processes. These ETDs are described because they represent promising targets for gene discovery related to clinical autistic traits, and they serve as models for analysis of separate candidate domains that may inform understanding of inherited etiological processes associated with ASD as well as overlapping neurodevelopmental disorders.

Mapping the evolution of regional brain network efficiency and its association with cognitive abilities during the first twenty-eight months of life

Human brain undergoes rapid growth during the first few years of life. While previous research has employed graph theory to study early brain development, it has mostly focused on the topological attributes of the whole brain. However, examining regional graph-theory features may provide unique insights into the development of cognitive abilities. Utilizing a large and longitudinal rsfMRI dataset from the UNC/UMN Baby Connectome Project, we investigated the developmental trajectories of regional efficiency and evaluated the relationships between these changes and cognitive abilities using Mullen Scales of Early Learning during the first twenty-eight months of life. Our results revealed a complex and spatiotemporally heterogeneous development pattern of regional global and local efficiency during this age period. Furthermore, we found that the trajectories of the regional global efficiency at the left temporal occipital fusiform and bilateral occipital fusiform gyri were positively associated with cognitive abilities, including visual reception, expressive language, receptive language, and early learning composite scores (P < 0.05, FDR corrected). However, these associations were weakened with age. These findings offered new insights into the regional developmental features of brain topologies and their associations with cognition and provided evidence of ongoing optimization of brain networks at both whole-brain and regional levels.

Confronting Epistemic Injustice and Inequity in IDD Research: The Value of Theorizing Beyond Dominant Culture's Perspective

This commentary highlights pervasive challenges related to the science of intellectual and developmental disabilities (IDD), which we often take for granted. We argue that social power asymmetry and entrenched patterns of epistemic injustices undermine our science and call attention to the need to maximize our efforts to undo these unfair practices to enhance future care and research in IDD.

Interactions between Bifidobacterium and Bacteroides and human milk oligosaccharides and their associations with infant cognition

While ample research on independent associations between infant cognition and gut microbiota composition and human milk (HM) oligosaccharides (HMOs) has been reported, studies on how the interactions between gut microbiota and HMOs may yield associations with cognitive development in infancy are lacking. We aimed to determine how HMOs and species of Bacteroides and Bifidobacterium genera interact with each other and their associations with cognitive development in typically developing infants. A total of 105 mother-infant dyads were included in this study. The enrolled infants [2.9-12 months old (8.09 ± 2.48)] were at least predominantly breastfed at 4 months old. A total of 170 HM samples from the mothers and fecal samples of the children were collected longitudinally. Using the Mullen Scales of Early Learning to assess cognition and the scores as the outcomes, linear mixed effects models including both the levels of eight HMOs and relative abundance of Bacteroides and Bifidobacterium species as main associations and their interactions were employed with adjusting covariates; infant sex, delivery mode, maternal education, site, and batch effects of HMOs. Additionally, regression models stratifying infants based on the A-tetrasaccharide (A-tetra) status of the HM they received were also employed to determine if the associations depend on the A-tetra status. With Bacteroides species, we observed significant associations with motor functions, while Bif. catenulatum showed a negative association with visual reception in the detectable A-tetra group both as main effect (value of p = 0.012) and in interaction with LNFP-I (value of p = 0.007). Additionally, 3-FL showed a positive association with gross motor (p = 0.027) and visual reception (p = 0.041). Furthermore, significant associations were observed with the interaction terms mainly in the undetectable A-tetra group. Specifically, we observed negative associations for Bifidobacterium species and LNT [breve (p = 0.011) and longum (p = 0.022)], and positive associations for expressive language with 3'-SL and Bif. bifidum (p = 0.01), 6'-SL and B. fragilis (p = 0.019), and LNFP-I and Bif. kashiwanohense (p = 0.048), respectively. Our findings suggest that gut microbiota and HMOs are both independently and interactively associated with early cognitive development. In particular, the diverse interactions between HMOs and Bacteroides and Bifidobacterium species reveal different candidate pathways through which HMOs, Bifidobacterium and Bacteroides species potentially interact to impact cognitive development in infancy.

BIBSNet: A Deep Learning Baby Image Brain Segmentation Network for MRI Scans

Objectives

Brain segmentation of infant magnetic resonance (MR) images is vitally important in studying developmental mental health and disease. The infant brain undergoes many changes throughout the first years of postnatal life, making tissue segmentation difficult for most existing algorithms. Here, we introduce a deep neural network BIBSNet (Baby and Infant Brain Segmentation Neural Network), an open-source, community-driven model that relies on data augmentation and a large sample size of manually annotated images to facilitate the production of robust and generalizable brain segmentations.

Experimental Design

Included in model training and testing were MR brain images on 84 participants with an age range of 0-8 months (median postmenstrual ages of 13.57 months). Using manually annotated real and synthetic segmentation images, the model was trained using a 10-fold cross-validation procedure. Testing occurred on MRI data processed with the DCAN labs infant-ABCD-BIDS processing pipeline using segmentations produced from gold standard manual annotation, joint-label fusion (JLF), and BIBSNet to assess model performance.

Principal Observations

Using group analyses, results suggest that cortical metrics produced using BIBSNet segmentations outperforms JLF segmentations. Additionally, when analyzing individual differences, BIBSNet segmentations perform even better.

Conclusions

BIBSNet segmentation shows marked improvement over JLF segmentations across all age groups analyzed. The BIBSNet model is 600x faster compared to JLF and can be easily included in other processing pipelines.

Quantifying latent social motivation and its associations with joint attention and language in infants at high and low likelihood for autism spectrum disorder

Social motivation-the psychobiological predisposition for social orienting, seeking social contact, and maintaining social interaction-manifests in early infancy and is hypothesized to be foundational for social communication development in typical and atypical populations. However, the lack of infant social-motivation measures has hindered delineation of associations between infant social motivation, other early-arising social abilities such as joint attention, and language outcomes. To investigate how infant social motivation contributes to joint attention and language, this study utilizes a mixed longitudinal sample of 741 infants at high (HL = 515) and low (LL = 226) likelihood for ASD. Using moderated nonlinear factor analysis (MNLFA), we incorporated items from parent-report measures to establish a novel latent factor model of infant social motivation that exhibits measurement invariance by age, sex, and familial ASD likelihood. We then examined developmental associations between 6- and 12-month social motivation, joint attention at 12-15 months, and language at 24 months of age. On average, greater social-motivation growth from 6-12 months was associated with greater initiating joint attention (IJA) and trend-level increases in sophistication of responding to joint attention (RJA). IJA and RJA were both positively associated with 24-month language abilities. There were no additional associations between social motivation and future language in our path model. These findings substantiate a novel, theoretically driven approach to modeling social motivation and suggest a developmental cascade through which social motivation impacts other foundational skills. These findings have implications for the timing and nature of intervention targets to support social communication development in infancy. HIGHLIGHTS: We describe a novel, theoretically based model of infant social motivation wherein multiple parent-reported indicators contribute to a unitary latent social-motivation factor. Analyses revealed social-motivation factor scores exhibited measurement invariance for a longitudinal sample of infants at high and low familial ASD likelihood. Social-motivation growth from ages 6-12 months is associated with better 12-15-month joint attention abilities, which in turn are associated with greater 24-month language skills. Findings inform timing and targets of potential interventions to support healthy social communication in the first year of life.

Responding to joint attention as a developmental catalyst: Longitudinal associations with language and social responsiveness

Joint attention (JA), infants' ability to engage in triadic attention with another person and a separate object or event, emerges in infancy. Responding to joint attention (RJA) develops earlier than initiating joint attention (IJA) and may benefit from a reconceptualization from a competence to a skill that varies in performance. Investigating associations between RJA performance and important skills of toddlerhood such as language, social responsiveness, and executive function (EF) in typically developing samples can better elucidate how RJA may serve as a developmental precursor to later dimensional skills, with implications for both typical and atypical development. Here, 210 (82% White) infants completed the Dimensional Joint Attention Assessment (DJAA), a naturalistic play-based assessment of RJA, at 8-15 months. At 16-38 months social responsiveness, verbal ability, and EF were assessed. Multilevel models showed that DJAA scores were associated with later verbal abilities and parent-reported social responsiveness. Exploratory analyses showed trend-level associations between RJA and EF. Results establish the content validity of the DJAA as a measure of RJA, and longitudinal associations with later verbal ability and social responsiveness. Future work should examine EF emergence and consolidation, and RJA and later EF associations.

A cybernetic theory of autism: Autism as a consequence of low trait plasticity

OBJECTIVE

According to Cybernetic Big Five Theory (CB5T), personality traits reflect variation in the parameters of evolved cybernetic mechanisms, and extreme manifestations of these traits correspond to a risk for psychopathology because they threaten the organism's ability to pursue its goals effectively. Our theory of autism as a consequence of low Plasticity extends CB5T to provide a cybernetic account of the origin of autistic traits. The theory argues that, because all psychological competencies are initially developed through exploration, typical development requires sensitivity to the incentive reward value of the unknown (i.e., the unpredicted). According to CB5T, motivation to explore the unknown is the core function underlying the metatrait Plasticity, the shared variance of Extraversion and Openness/Intellect. This theory makes predictions regarding the downstream developmental consequences of early low Plasticity, and each prediction maps well onto autistic symptomatology.

METHOD

We surveyed 387 people. Measures included the Autism Quotient (AQ) scale and International Personality Item Pool items that are indicators of Plasticity and Stability.

RESULTS

The association between AQ and Plasticity was β = -.64.

CONCLUSION

A strong negative correlation between Plasticity and AQ suggests ASD may be closely linked to a low sensitivity to the incentive reward value of the unknown.

Creating a sustainable action-oriented engagement infrastructure-a UMN-MIDB perspective

Following the murder of George Floyd on May 25, 2020, Minneapolis represented the epicenter of protests that would reverberate internationally and re-instantiate a reckoning of the systemic and institutional racism that plagues American society. Also in the summer of 2020, and after several years of planning, the University of Minnesota (UMN) launched the Masonic Institute for the Developing Brain (MIDB), an interdisciplinary clinical and community research enterprise designed to create knowledge and engage all members of our community. In what follows, we describe the mission of the MIDB Community Engagement and Education (CEEd) Core and adjacent efforts within the UMN neuroscience and psychology community. Inherent to these efforts is the explicit attempt to de-center the dominant academic voice and affirm knowledge creation is augmented by diverse voices within and outside of traditional academic institutions. We describe several initiatives, including the Neuroscience Opportunities for Discovery and Equity (NODE) network, the NextGen Psych Scholars Program (NPSP), the Young Scientist Program, among others as exemplars of our approach. Developing and fortifying sustainable pathways for authentic community-academic partnerships are of central importance to enhance mutually beneficial scientific discovery. We posit that traditional academic approaches to community engagement to benefit the institution are severely constrained and perpetuate inherently exploitative power dynamics between academic institutions and communities.

A Data-Driven Approach in an Unbiased Sample Reveals Equivalent Sex Ratio of Autism Spectrum Disorder-Associated Impairment in Early Childhood

BACKGROUND

Sex differences in the prevalence of neurodevelopmental disorders are particularly evident in autism spectrum disorder (ASD). Heterogeneous symptom presentation and the potential of measurement bias hinder early ASD detection in females and may contribute to discrepant prevalence estimates. We examined trajectories of social communication (SC) and restricted and repetitive behaviors (RRBs) in a sample of infant siblings of children with ASD, adjusting for age- and sex-based measurement bias. We hypothesized that leveraging a prospective elevated familial likelihood sample, deriving data-driven behavioral constructs, and accounting for measurement bias would reveal less discrepant sex ratios than are typically seen in ASD.

METHODS

We conducted direct assessments of ASD symptoms at 6 to 9, 12 to 15, 24, and 36 to 60 months of age (total nobservations = 1254) with infant siblings of children with ASD (n = 377) and a lower ASD-familial-likelihood comparison group (n = 168; nobservations = 527). We established measurement invariance across age and sex for separate models of SC and RRB. We then conducted latent class growth mixture modeling with the longitudinal data and evaluated for sex differences in trajectory membership.

RESULTS

We identified 2 latent classes in the SC and RRB models with equal sex ratios in the high-concern cluster for both SC and RRB. Sex differences were also observed in the SC high-concern cluster, indicating that girls classified as having elevated social concerns demonstrated milder symptoms than boys in this group.

CONCLUSIONS

This novel approach for characterizing ASD symptom progression highlights the utility of assessing and adjusting for sex-related measurement bias and identifying sex-specific patterns of symptom emergence.

Examining the factor structure and discriminative utility of the Infant Behavior Questionnaire-Revised in infant siblings of autistic children

Using the Infant Behavior Questionnaire-Revised in a longitudinal sample of infant siblings of autistic children (HR; n = 427, 171 female, 83.4% White) and a comparison group of low-risk controls (LR, n = 200, 86 female, 81.5% White), collected between 2007 and 2017, this study identified an invariant factor structure of temperament traits across groups at 6 and 12 months. Second, after partitioning the groups by familial risk and diagnostic outcome at 24 months, results reveal an endophenotypic pattern of Positive Emotionality at both 6 and 12 months, (HR-autism spectrum disorder [ASD] < HR-no-ASD < LR). Third, increased 'Duration of Orienting' at 12 months was associated with lower scores on the 24-month developmental outcomes in HR infants. These findings may augment efforts for early identification of ASD.

Joint analyses of human milk fatty acids, phospholipids, and choline in association with cognition and temperament traits during the first 6 months of life

Early dietary exposure via human milk nutrients offers a window of opportunity to support cognitive and temperament development. While several studies have focused on associations of few pre-selected human milk nutrients with cognition and temperament, it is highly plausible that human milk nutrients synergistically and jointly support cognitive and behavioral development in early life. We aimed to discern the combined associations of three major classes of human milk nutrients with cognition and temperament during the first 6 months of life when human milk is the primary source of an infant’s nutrition and explore whether there were persistent effects up to 18 months old. The Mullen Scales of Early Learning and Infant Behavior Questionnaires—Revised were used to assess cognition and temperament, respectively, of 54 exclusively/predominantly breastfed infants in the first 6 months of life, whose follow-ups were conducted at 6–9, 9–12, and 12–18 months old. Human milk samples were obtained from the mothers of the participants at less than 6 months of age and analyzed for fatty acids [total monounsaturated fatty acids, polyunsaturated fatty acid, total saturated fatty acid (TSFA), arachidonic acid (ARA), docosahexaenoic acid (DHA), ARA/DHA, omega-6/omega-3 polyunsaturated fatty acids ratio (n-6/n-3)], phospholipids [phosphatidylcholine, phosphatidylethanolamine (PE), phosphatidylinositol (PI), sphingomyelin], and choline [free choline, phosphocholine (PCho), glycerophosphocholine]. Feature selection was performed to select nutrients associated with cognition and temperament. The combined effects of selected nutrients were analyzed using multiple regression. A positive association between the arachidonic acid (ARA) and surgency was observed (p = 0.024). A significant effect of DHA, n-6/n-3, PE, and TSFA concentrations on receptive language (R² = 0.39, p = 0.025) and the elevated ARA, PCho, and PI with increased surgency (R² = 0.43, p = 0.003) was identified, suggesting that DHA and ARA may have distinct roles for temperament and language functions. Furthermore, the exploratory association analyses suggest that the effects of human milk nutrients on R.L. and surgency may persist beyond the first 6 months of life, particularly surgency at 12–18 months (p = 0.002). Our study highlighted that various human milk nutrients work together to support the development of cognition and temperament traits during early infancy.

Infant Visual Brain Development and Inherited Genetic Liability in Autism

OBJECTIVE

Autism spectrum disorder (ASD) is heritable, and younger siblings of ASD probands are at higher likelihood of developing ASD themselves. Prospective MRI studies of siblings report that atypical brain development precedes ASD diagnosis, although the link between brain maturation and genetic factors is unclear. Given that familial recurrence of ASD is predicted by higher levels of ASD traits in the proband, the authors investigated associations between proband ASD traits and brain development among younger siblings.

METHODS

In a sample of 384 proband-sibling pairs (89 pairs concordant for ASD), the authors examined associations between proband ASD traits and sibling brain development at 6, 12, and 24 months in key MRI phenotypes: total cerebral volume, cortical surface area, extra-axial cerebrospinal fluid, occipital cortical surface area, and splenium white matter microstructure. Results from primary analyses led the authors to implement a data-driven approach using functional connectivity MRI at 6 months.

RESULTS

Greater levels of proband ASD traits were associated with larger total cerebral volume and surface area and larger surface area and reduced white matter integrity in components of the visual system in siblings who developed ASD. This aligned with weaker functional connectivity between several networks and the visual system among all siblings during infancy.

CONCLUSIONS

The findings provide evidence that specific early brain MRI phenotypes of ASD reflect quantitative variation in familial ASD traits. Multimodal anatomical and functional convergence on cortical regions, fiber pathways, and functional networks involved in visual processing suggest that inherited liability has a role in shaping the prodromal development of visual circuitry in ASD.

Resting-state functional connectivity identifies individuals and predicts age in 8-to-26-month-olds

Resting-state functional connectivity (rsFC) measured with fMRI has been used to characterize functional brain maturation in typically and atypically developing children and adults. However, its reliability and utility for predicting development in infants and toddlers is less well understood. Here, we use fMRI data from the Baby Connectome Project study to measure the reliability and uniqueness of rsFC in infants and toddlers and predict age in this sample (8-to-26 months old; n = 170). We observed medium reliability for within-session infant rsFC in our sample, and found that individual infant and toddler's connectomes were sufficiently distinct for successful functional connectome fingerprinting. Next, we trained and tested support vector regression models to predict age-at-scan with rsFC. Models successfully predicted novel infants' age within ± 3.6 months error and a prediction R² = .51. To characterize the anatomy of predictive networks, we grouped connections into 11 infant-specific resting-state functional networks defined in a data-driven manner. We found that connections between regions of the same network-i.e. within-network connections-predicted age significantly better than between-network connections. Looking ahead, these findings can help characterize changes in functional brain organization in infancy and toddlerhood and inform work predicting developmental outcome measures in this age range.

Subcortical Brain Development in Autism and Fragile X Syndrome: Evidence for Dynamic, Age- and Disorder-Specific Trajectories in Infancy

OBJECTIVE

Previous research has demonstrated that the amygdala is enlarged in children with autism spectrum disorder (ASD). However, the precise onset of this enlargement during infancy, how it relates to later diagnostic behaviors, whether the timing of enlargement in infancy is specific to the amygdala, and whether it is specific to ASD (or present in other neurodevelopmental disorders, such as fragile X syndrome) are all unknown.

METHODS

Longitudinal MRIs were acquired at 6-24 months of age in 29 infants with fragile X syndrome, 58 infants at high likelihood for ASD who were later diagnosed with ASD, 212 high-likelihood infants not diagnosed with ASD, and 109 control infants (1,099 total scans).

RESULTS

Infants who developed ASD had typically sized amygdala volumes at 6 months, but exhibited significantly faster amygdala growth between 6 and 24 months, such that by 12 months the ASD group had significantly larger amygdala volume (Cohen's d=0.56) compared with all other groups. Amygdala growth rate between 6 and 12 months was significantly associated with greater social deficits at 24 months when the infants were diagnosed with ASD. Infants with fragile X syndrome had a persistent and significantly enlarged caudate volume at all ages between 6 and 24 months (d=2.12), compared with all other groups, which was significantly associated with greater repetitive behaviors.

CONCLUSIONS

This is the first MRI study comparing fragile X syndrome and ASD in infancy, demonstrating strikingly different patterns of brain and behavior development. Fragile X syndrome-related changes were present from 6 months of age, whereas ASD-related changes unfolded over the first 2 years of life, starting with no detectable group differences at 6 months. Increased amygdala growth rate between 6 and 12 months occurs prior to social deficits and well before diagnosis. This gradual onset of brain and behavior changes in ASD, but not fragile X syndrome, suggests an age- and disorder-specific pattern of cascading brain changes preceding autism diagnosis.

Comparison of U.S. and Tajik infants' time in containment devices

How infants are held or contained throughout the day shape infants' experiences, particularly around movement and exploration. In Tajikistan, caregivers use "gahvora" cradles, which severely restrict the body and limbs. The present study explored the variability and use of containment devices in U.S. and Tajik infants. Using time diaries, we compared 12-month-olds in the U.S. and Tajikistan on the types of containments used and time spent in them throughout the day. During the day, Tajik infants accumulated more time in gahvoras than infants in the U.S. spent in cribs, primarily used for sleep, suggesting gahvoras served other functions. Given the availability of other devices, U.S. infants' time was distributed in short yet frequent bouts across devices. Accumulated time in these containments matched accumulated time Tajik infants spent in gahvoras. Tajik infants accumulated more unrestricted time on the ground, which was distributed in prolonged bouts, than U.S. infants. Findings highlight differences in infants' everyday experiences during the developmental period when motor skills emerge. By embracing commonalities and exploring differences between cultures, this study offers insights into differences in infants' everyday experiences and opportunities for movement.

Learning Strategies for Contrast-agnostic Segmentation via SynthSeg for Infant MRI data

Longitudinal studies of infants' brains are essential for research and clinical detection of neurodevelopmental disorders. However, for infant brain MRI scans, effective deep learning-based segmentation frameworks exist only within small age intervals due to the large image intensity and contrast changes that take place in the early postnatal stages of development. However, using different segmentation frameworks or models at different age intervals within the same longitudinal data set would cause segmentation inconsistencies and age-specific biases. Thus, an age-agnostic segmentation model for infants' brains is needed. In this paper, we present "Infant-SynthSeg", an extension of the contrast-agnostic SynthSeg segmentation framework applicable to MRI data of infants at ages within the first year of life. Our work mainly focuses on extending learning strategies related to synthetic data generation and augmentation, with the aim of creating a method that employs training data capturing features unique to infants' brains during this early-stage development. Comparison across different learning strategy settings, as well as a more-traditional contrast-aware deep learning model (nnU-net) are presented. Our experiments show that our trained Infant-SynthSeg models show consistently high segmentation performance on MRI scans of infant brains throughout the first year of life. Furthermore, as the model is trained on ground truth labels at different ages, even labels that are not present at certain ages (such as cerebellar white matter at 1 month) can be appropriately segmented via Infant-SynthSeg across the whole age range. Finally, while Infant-SynthSeg shows consistent segmentation performance across the first year of life, it is outperformed by age-specific deep learning models trained for a specific narrow age range.

Synthesizing pseudo-T2w images to recapture missing data in neonatal neuroimaging with applications in rs-fMRI

T1- and T2-weighted (T1w and T2w) images are essential for tissue classification and anatomical localization in Magnetic Resonance Imaging (MRI) analyses. However, these anatomical data can be challenging to acquire in non-sedated neonatal cohorts, which are prone to high amplitude movement and display lower tissue contrast than adults. As a result, one of these modalities may be missing or of such poor quality that they cannot be used for accurate image processing, resulting in subject loss. While recent literature attempts to overcome these issues in adult populations using synthetic imaging approaches, evaluation of the efficacy of these methods in pediatric populations and the impact of these techniques in conventional MR analyses has not been performed. In this work, we present two novel methods to generate pseudo-T2w images: the first is based in deep learning and expands upon previous models to 3D imaging without the requirement of paired data, the second is based in nonlinear multi-atlas registration providing a computationally lightweight alternative. We demonstrate the anatomical accuracy of pseudo-T2w images and their efficacy in existing MR processing pipelines in two independent neonatal cohorts. Critically, we show that implementing these pseudo-T2w methods in resting-state functional MRI analyses produces virtually identical functional connectivity results when compared to those resulting from T2w images, confirming their utility in infant MRI studies for salvaging otherwise lost subject data.

A broadened estimate of syntactic and lexical ability from the MB-CDI

A critical question in the study of language development is to understand lexical and syntactic acquisition, which play different roles in speech to the extent it would be natural to surmise they are acquired differently. As measured through the comprehension and production of closed-class words, syntactic ability emerges at roughly the 400-word mark. However, a significant proportion of the developmental work uses a coarse combination of function and content words on the MacArthur-Bates Communicative Development Inventory (MB-CDI). Using the MB-CDI Wordbank database, we implemented a factor analytic approach to distinguish between lexical and syntactic development from the Words and Sentences (WS) form that involves both function words and the explicit categorizations. Although the Words and Gestures (WG) form did not share the factor structure, common WG/WS elements recapitulate the expected age-related changes. This parsing of the MB-CDI may prove simple, yet fruitful in subsequent investigation.

Real-time motion monitoring improves functional MRI data quality in infants

Imaging the infant brain with MRI has improved our understanding of early neurodevelopment. However, head motion during MRI acquisition is detrimental to both functional and structural MRI scan quality. Though infants are typically scanned while asleep, they commonly exhibit motion during scanning causing data loss. Our group has shown that providing MRI technicians with real-time motion estimates via Framewise Integrated Real-Time MRI Monitoring (FIRMM) software helps obtain high-quality, low motion fMRI data. By estimating head motion in real time and displaying motion metrics to the MR technician during an fMRI scan, FIRMM can improve scanning efficiency. Here, we compared average framewise displacement (FD), a proxy for head motion, and the amount of usable fMRI data (FD ≤ 0.2 mm) in infants scanned with (n = 407) and without FIRMM (n = 295). Using a mixed-effects model, we found that the addition of FIRMM to current state-of-the-art infant scanning protocols significantly increased the amount of usable fMRI data acquired per infant, demonstrating its value for research and clinical infant neuroimaging.

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MRI studies of the infant brain are critical for studying early neurodevelopment.

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Head motion diminishes MRI data quality, which can adversely affect infant imaging.

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We show that real-time head motion monitoring improves fMRI scan quality in infants.

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Being able to monitor motion during fMRI acquisition improves scanning efficiency.

Brain charts for the human lifespan

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.

Variability in Responding to Joint Attention Cues in the First Year is Associated With Autism Outcome

OBJECTIVE

With development, infants become increasingly responsive to the many attention-sharing cues of adults; however, little work has examined how this ability emerges in typical development or in the context of early autism spectrum disorder (ASD). This study characterized variation in the type of cue needed to elicit a response to joint attention (RJA) using the Dimensional Joint Attention Assessment (DJAA) during naturalistic play.

METHOD

We measured the average redundancy of cue type required for infants to follow RJA bids from an experimenter, as well as their response consistency, in 268 infants at high (HR, n = 68) and low (LR, N = 200) familial risk for ASD. Infants were assessed between 8 and 18 months of age and followed up with developmental and clinical assessments at 24 or 36 months. Our sample consisted of LR infants, as well as HR infants who did (HR-ASD) and did not (HR-neg) develop ASD at 24 months.

RESULTS

We found that HR and LR infants developed abilities to respond to less redundant (more sophisticated) RJA cues at different rates, and that HR-ASD infants displayed delayed abilities, identifiable as early as 9 months, compared to both HR-neg and LR infants. Interestingly, results suggest that HR-neg infants may exhibit a propensity to respond to less redundant (more sophisticated) RJA cues relative to both HR-ASD and LR infants.

CONCLUSION

Using an approach to characterize variable performance of RJA cue-reading abilities, findings from this study enhance our understanding of both typical and ASD-related proficiencies and deficits in RJA development.

Filtering respiratory motion artifact from resting state fMRI data in infant and toddler populations

The importance of motion correction when processing resting state functional magnetic resonance imaging (rs-fMRI) data is well-established in adult cohorts. This includes adjustments based on self-limited, large amplitude subject head motion, as well as factitious rhythmic motion induced by respiration. In adults, such respiration artifact can be effectively removed by applying a notch filter to the motion trace, resulting in higher amounts of data retained after frame censoring (e.g., "scrubbing") and more reliable correlation values. Due to the unique physiological and behavioral characteristics of infants and toddlers, rs-fMRI processing pipelines, including methods to identify and remove colored noise due to subject motion, must be appropriately modified to accurately reflect true neuronal signal. These younger cohorts are characterized by higher respiration rates and lower-amplitude head movements than adults; thus, the presence and significance of comparable respiratory artifact and the subsequent necessity of applying similar techniques remain unknown. Herein, we identify and characterize the consistent presence of respiratory artifact in rs-fMRI data collected during natural sleep in infants and toddlers across two independent cohorts (aged 8-24 months) analyzed using different pipelines. We further demonstrate how removing this artifact using an age-specific notch filter allows for both improved data quality and data retention in measured results. Importantly, this work reveals the critical need to identify and address respiratory-driven head motion in fMRI data acquired in young populations through the use of age-specific motion filters as a mechanism to optimize the accuracy of measured results in this population.

Sex differences in age of diagnosis of autism spectrum disorder: Preliminary evidence from Uganda

This study was performed to determine (a) the age at which autism spectrum disorder (ASD) is first diagnosed in Ugandan children receiving mental health services, (b) whether age at diagnosis varies by sex and clinical presentation, and (c) the average age of ASD diagnosis in children manifesting comorbid conditions. A retrospective chart review was performed and demographic as well as clinical data were collected from children with ASD diagnoses who attended two mental health clinics in Uganda between 2014 and 2019. Descriptive statistics such as percentages, means, and standard deviations were used to summarize the data. Independent t-test was also performed to determine differences in the mean age of diagnosis between males and females. Two hundred and thirty-seven (156 males, 81 females) children with ASD were identified. The average age of ASD diagnosis was (6.9 ± 4.0) years. A statistically significant difference in age of ASD diagnosis was found between males and females (t = -2.106, p = 0.036), such that on average females received a diagnosis at least 1 year later than males. Of the 237 participants, 53.6% were identified with ASD only, 16.0% had ASD and ADHD, 10.5% were diagnosed with ASD and epilepsy, and 7.2% had a diagnosis of complex ASD. The results confirm delays in access to ASD diagnosis and suggest that females are more likely to receive a ASD diagnosis later than males within the Ugandan context. ASD awareness should be intensified to improve public or professional knowledge about ASD to enhance early identification in Uganda.

Diagnostic shifts in autism spectrum disorder can be linked to the fuzzy nature of the diagnostic boundary: a data-driven approach

BACKGROUND

Diagnostic shifts at early ages may provide invaluable insights into the nature of separation between autism spectrum disorder (ASD) and typical development. Recent conceptualizations of ASD suggest the condition is only fuzzily separated from non-ASD, with intermediate cases between the two. These intermediate cases may shift along a transition region over time, leading to apparent instability of diagnosis.

METHODS

We used a cohort of children with high ASD risk, by virtue of having an older sibling with ASD, assessed at 24 months (N = 212) and 36 months (N = 191). We applied machine learning to empirically characterize the classification boundary between ASD and non-ASD, using variables quantifying developmental and adaptive skills. We computed the distance of children to the classification boundary.

RESULTS

Children who switched diagnostic labels from 24 to 36 months, in both directions, (dynamic group) had intermediate phenotypic profiles. They were closer to the classification boundary compared to children who had stable diagnoses, both at 24 months (Cohen's d = .52) and at 36 months (d = .75). The magnitude of change in distance between the two time points was similar for the dynamic and stable groups (Cohen's d = .06), and diagnostic shifts were not associated with a large change. At the individual level, a few children in the dynamic group showed substantial change.

CONCLUSIONS

Our results suggested that a diagnostic shift was largely due to a slight movement within a transition region between ASD and non-ASD. This fact highlights the need for more vigilant surveillance and intervention strategies. Young children with intermediate phenotypes may have an increased susceptibility to gain or lose their diagnosis at later ages, calling attention to the inherently dynamic nature of early ASD diagnoses.

Emerging ethical issues raised by highly portable MRI research in remote and resource-limited international settings

Smaller, more affordable, and more portable MRI brain scanners offer exciting opportunities to address unmet research needs and long-standing health inequities in remote and resource-limited international settings. Field-based neuroimaging research in low- and middle-income countries (LMICs) can improve local capacity to conduct both structural and functional neuroscience studies, expand knowledge of brain injury and neuropsychiatric and neurodevelopmental disorders, and ultimately improve the timeliness and quality of clinical diagnosis and treatment around the globe. Facilitating MRI research in remote settings can also diversify reference databases in neuroscience, improve understanding of brain development and degeneration across the lifespan in diverse populations, and help to create reliable measurements of infant and child development. These deeper understandings can lead to new strategies for collaborating with communities to mitigate and hopefully overcome challenges that negatively impact brain development and quality of life. Despite the potential importance of research using highly portable MRI in remote and resource-limited settings, there is little analysis of the attendant ethical, legal, and social issues (ELSI). To begin addressing this gap, this paper presents findings from the first phase of an envisioned multi-staged and iterative approach for creating ethical and legal guidance in a complex global landscape. Section 1 provides a brief introduction to the emerging technology for field-based MRI research. Section 2 presents our methodology for generating plausible use cases for MRI research in remote and resource-limited settings and identifying associated ELSI issues. Section 3 analyzes core ELSI issues in designing and conducting field-based MRI research in remote, resource-limited settings and offers recommendations. We argue that a guiding principle for field-based MRI research in these contexts should be including local communities and research participants throughout the research process in order to create sustained local value. Section 4 presents a recommended path for the next phase of work that could further adapt these use cases, address ethical and legal issues, and co-develop guidance in partnership with local communities.

Cataloguing and characterizing interests in typically developing toddlers and toddlers who develop ASD

Intense interests are common in children with and without autism spectrum disorder (ASD), and little research has characterized aspects of interests that are unique to or shared among children with and without ASD. We aimed to characterize interests in a sample of infants at high-familial-risk (HR) and low-familial-risk (LR) for ASD using a novel interview. Participants included HR siblings who were diagnosed with ASD at 24 months (HR-ASD, n = 56), HR siblings who did not receive an ASD diagnosis at 24 months (HR-Neg, n = 187), and a LR comparison group (n = 109). We developed and collected data with the Intense Interests Inventory at 18- and 24-months of age, a semi-structured interview that measures intensity and peculiarity of interests in toddlers and preschool-aged children. Intensity of interests differed by familial risk at 24 months, with HR-ASD and HR-Neg groups demonstrating equivalent intensity of interests that were higher than the LR group. By contrast, peculiarity of interest differed by ASD diagnosis, with the HR-ASD group showing more peculiar interests than the HR-Neg and LR groups at 24 months. At 18 months the HR-ASD group had more peculiar interests than the LR group, though no differences emerged in intensity of interests. This measure may be useful in identifying clinically-relevant features of interests in young children with ASD. We also replicated previous findings of males showing more intense interests at 18 months in our non-ASD sample. These results reveal new information about the nature of interests and preoccupations in the early autism phenotype. LAY SUMMARY: Intense interests are common in young children with autism and their family members. Intense interests are also prevalent among typically-developing children, and especially boys. Here we catalog interests and features of these interests in a large sample of toddlers enriched for autism risk. Children who had family members with autism had more intense interests, and those who developed autism themselves had more unusual interests at 24 months. These results highlight the importance of different aspects of interest in autism.

Towards a Data-Driven Approach to Screen for Autism Risk at 12 Months of Age

OBJECTIVE

This study aimed to develop a classifier for infants at 12 months of age based on a parent-report measure (the First Year Inventory 2.0 [FYI]), for the following reasons: (1) to classify infants at elevated risk, above and beyond that attributable to familial risk status for ASD; and (2) to serve as a starting point to refine an approach for risk estimation in population samples.

METHOD

A total of 54 high-familial risk (HR) infants later diagnosed with ASD (HR-ASD), 183 HR infants not diagnosed with ASD at 24 months of age (HR-Neg), and 72 low-risk controls participated in the study. All infants contributed FYI data at 12 months of age and had a diagnostic assessment for ASD at age 24 months. A data-driven, cross-validated analytic approach was used to develop a classifier to determine screening accuracy (eg, sensitivity) of the FYI to classify HR-ASD and HR-Neg.

RESULTS

The newly developed FYI classifier had an estimated sensitivity of 0.71 (95% CI: 0.50, 0.91) and specificity of 0.72 (95% CI: 0.49, 0.91).

CONCLUSION

This classifier demonstrates the potential to improve current screening for ASD risk at 12 months of age in infants already at elevated familial risk for ASD, increasing opportunities for detection of autism risk in infancy. Findings from this study highlight the utility of combining parent-report measures with machine learning approaches.

Phenoscreening: a developmental approach to research domain criteria-motivated sampling

BACKGROUND

To advance early identification efforts, we must detect and characterize neurodevelopmental sequelae of risk among population-based samples early in development. However, variability across the typical-to-atypical continuum and heterogeneity within and across early emerging psychiatric/neurodevelopmental disorders represent fundamental challenges to overcome. Identifying multidimensionally determined profiles of risk, agnostic to DSM categories, via data-driven computational approaches represents an avenue to improve early identification of risk.

METHODS

Factor mixture modeling (FMM) was used to identify subgroups and characterize phenotypic risk profiles, derived from multiple parent-report measures of typical and atypical behaviors common to autism spectrum disorder, in a community-based sample of 17- to 25-month-old toddlers (n = 1,570). To examine the utility of risk profile classification, a subsample of toddlers (n = 107) was assessed on a distal, independent outcome examining internalizing, externalizing, and dysregulation at approximately 30 months.

RESULTS

FMM results identified five asymmetrically sized subgroups. The putative high- and moderate-risk groups comprised 6% of the sample. Follow-up analyses corroborated the utility of the risk profile classification; the high-, moderate-, and low-risk groups were differentially stratified (i.e., HR > moderate-risk > LR) on outcome measures and comparison of high- and low-risk groups revealed large effect sizes for internalizing (d = 0.83), externalizing (d = 1.39), and dysregulation (d = 1.19).

CONCLUSIONS

This data-driven approach yielded five subgroups of toddlers, the utility of which was corroborated by later outcomes. Data-driven approaches, leveraging multiple developmentally appropriate dimensional RDoC constructs, hold promise for future efforts aimed toward early identification of at-risk-phenotypes for a variety of early emerging neurodevelopmental disorders.

Human milk 3'-Sialyllactose is positively associated with language development during infancy

BACKGROUND

Genetic polymorphisms leading to variations in human milk oligosaccharide (HMO) composition have been reported. Alpha-Tetrasaccharide (A-tetra), an HMO, has been shown to only be present (>limit of detection; A-tetra+) in the human milk (HM) of women with blood type A, suggesting genetic origins determining the presence or absence (A-tetra-) of A-tetra in HM.

OBJECTIVES

This study aimed to determine whether associations exist between HMO concentrations and cognitive development, and whether the associations vary between A-tetra+ and A-tetra- groups in children (<25 months old).

METHODS

We enrolled typically developing children (2-25 months old; mean, 10 months old) who were at least partially breastfed at the study visit. The Mullen Scales of Early Learning (MSEL) were used as the primary outcome measure to assess early cognitive development. Linear mixed effects models were employed by stratifying children based on A-tetra levels (A-tetra+ or A-tetra-) to assess associations between age-removed HMO concentrations and both MSEL composite scores and the 5 subdomain scores.

RESULTS

A total of 99 mother-child dyads and 183 HM samples were included (A-tetra+: 57 samples, 33 dyads; A-tetra-: 126 samples, 66 dyads). No significant association was observed between HMOs and MSEL when all samples were analyzed together. The composite score and 3'-sialyllactose (3'-SL) levels were positively associated [P = 0.002; effect size (EF), 13.12; 95% CI, 5.36-20.80] in the A-tetra + group. This association was driven by the receptive (adjusted P = 0.015; EF, 9.95; 95% CI, 3.91-15.99) and expressive (adjusted P = 0.048; EF, 7.53; 95% CI, 2.51-13.79) language subdomain scores. Furthermore, there was an interaction between 3'-SL and age for receptive language (adjusted P = 0.03; EF, -14.93; 95% CI, -25.29 to -4.24).

CONCLUSIONS

Our study reports the association of 3'-SL and cognition, particularly language functions, in typically developing children who received HM containing detectable A-tetra during infancy.

Visual input to the left versus right eye yields differences in face preferences in 3-month-old infants

From birth, infants prefer looking at faces over scrambled faces. This face input is important for the development of face processing: individuals who experienced early visual deprivation due to congenital cataracts have long-lasting face processing deficits. Interestingly, the deficits are eye-specific such that left eye cataracts disrupt the development of face processing, whereas right eye cataracts do not. This raises the question of whether infant face preferences are driven primarily by faces observed through the left eye. To investigate this, we presented 3-month-old infants with intact faces paired with scrambled faces. Infants viewed the moving stimuli binocularly, only with their left eye, or only with their right eye. Infants viewing stimuli binocularly or with only the left eye spent significantly more time looking at intact faces than scrambled faces, but this effect was equivocal in infants viewing stimuli through only their right eye. Infants in the binocular group had the greatest preference for faces, and this preference was greater than the right eye group's preference for faces. The left eye group's preference for faces was not statistically different from the other two groups' preference for faces, but additional analyses revealed a correlation between preference for faces and age for the right eye group only, indicating that preference for faces seen with the right eye increase from 3 to 4 months of age. These results indicate that the left eye plays a special role in face processing at, or before 3 months of age, but a preference for faces through the right eye emerges soon after.

Infants' abilities to respond to cues for joint attention vary by family socioeconomic status

The influence of socioeconomic variability on language and cognitive development is present from toddlerhood to adolescence and calls for investigating its earliest manifestation. Response to joint attention (RJA) abilities constitute a foundational developmental milestone that are associated with future language, cognitive, and social skills. How aspects of the family home environment shape RJA skills is relatively unknown. We investigated associations between family socioeconomic status (SES) -both parent education and family percentage of the federal poverty level (FPL)- parent depressive and anxiety symptoms and infant RJA performance in a cross-sectional sample of 173 infants aged 8-18 months and their parents from a variety of socioeconomic backgrounds. Results suggest that, correcting for age and receptive language, infants in families with greater economic resources respond to relatively less redundant, more sophisticated cues for joint attention. Although parent depressive and anxiety symptoms are negatively correlated with SES, parent depressive and anxiety symptoms were not associated with infant RJA. These findings provide evidence of SES-related differences in social cognitive development as early as infancy, calling on policymakers to address the inequities in the current socioeconomic landscape of the United States.

Longitudinal change in restricted and repetitive behaviors from 8-36 months

BACKGROUND

Restricted and repetitive behaviors (RRBs) are core features of autism spectrum disorder (ASD) and one of the earliest behavioral signs of ASD. However, RRBs are also present in typically developing (TD) infants, toddlers, and preschool-aged children. Past work suggests that examining change in these behaviors over time is essential to distinguish between normative manifestations of these behaviors and behaviors that denote risk for a neurodevelopmental disorder. One challenge in examining changes in these behaviors over time is that most measures of RRBs have not established longitudinal measurement invariance. The aims of this study were to (1) establish measurement invariance in the Repetitive Behavior Scales for Early Childhood (RBS-EC), a parent-report questionnaire of RRBs, and (2) model developmental change in RRBs from 8 to 36 months.

METHODS

We collected RBS-EC responses from parents of TD infants (n = 180) from 8 to 36 months (n = 606 responses, with participants contributing an average of 3-time points). We leverage a novel methodological approach to measurement invariance testing (Bauer, Psychological Models, 22(3), 507-526, 2017), moderated nonlinear factor analysis (MNLFA), to determine whether the RBS-EC was invariant across age and sex. We then generated adjusted factor score estimates for each subscale of the RBS-EC (repetitive motor, self-directed, and higher-order behaviors), and used linear mixed effects models to estimate between- and within-person changes in the RBS-EC over time.

RESULTS

The RBS-EC showed some non-invariance as a function of age. We were able to adjust for this non-invariance in order to more accurately model changes in the RBS-EC over time. Repetitive motor and self-directed behaviors showed a linear decline from 8 to 36 months, while higher-order behaviors showed a quadratic trajectory such that they began to decline later in development at around 18 months. Using adjusted factor scores as opposed to unadjusted raw mean scores provided a number of benefits, including increased within-person variability and precision.

CONCLUSIONS

The RBS-EC is sensitive enough to measure the presence of RRBs in a TD sample, as well as their decline with age. Using factor score estimates of each subscale adjusted for non-invariance allowed us to more precisely estimate change in these behaviors over time.

Measurement of Cognition for the National Children's Study

The National Children's Study Cognitive Health Domain Team developed detailed plans for assessing cognition longitudinally from infancy to early adulthood. These plans identify high-priority aspects of cognition that can be measured efficiently and effectively, and we believe they can serve as a model for future large-scale longitudinal research. For infancy and toddlerhood, we proposed several paradigms that collectively allowed us to assess six broad cognitive constructs: (1) executive function skills, (2) episodic memory, (3) language, (4) processing speed, (5) spatial and numerical processing, and (6) social cognition. In some cases, different trial sequences within a paradigm allow for the simultaneous assessment of multiple cognitive skills (e.g., executive function skills and processing speed). We define each construct, summarize its significance for understanding developmental outcomes, discuss the feasibility of its assessment throughout development, and present our plan for measuring specific skills at different ages. Given the need for well-validated, direct behavioral measures of cognition that can be used in large-scale longitudinal studies, especially from birth to age 3 years, we also initiated three projects focused on the development of new measures.

A voxel-wise assessment of growth differences in infants developing autism spectrum disorder

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Pediatric neuroimaging study of Autism Spectrum Disorder.

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Longitudinal Tensor Based Morphometry of the presymptomatic period of ASD.

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Differences in voxelwise growth trajectories of children with ASD.

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Regions with differences have been implicated in the core symptoms of ASD.

Autism Spectrum Disorder (ASD) is a phenotypically and etiologically heterogeneous developmental disorder typically diagnosed around 4 years of age. The development of biomarkers to help in earlier, presymptomatic diagnosis could facilitate earlier identification and therefore earlier intervention and may lead to better outcomes, as well as providing information to help better understand the underlying mechanisms of ASD. In this study, magnetic resonance imaging (MRI) scans of infants at high familial risk, from the Infant Brain Imaging Study (IBIS), at 6, 12 and 24 months of age were included in a morphological analysis, fitting a mixed-effects model to Tensor Based Morphometry (TBM) results to obtain voxel-wise growth trajectories. Subjects were grouped by familial risk and clinical diagnosis at 2 years of age. Several regions, including the posterior cingulate gyrus, the cingulum, the fusiform gyrus, and the precentral gyrus, showed a significant effect for the interaction of group and age associated with ASD, either as an increased or a decreased growth rate of the cerebrum. In general, our results showed increased growth rate within white matter with decreased growth rate found mostly in grey matter. Overall, the regions showing increased growth rate were larger and more numerous than those with decreased growth rate. These results detail, at the voxel level, differences in brain growth trajectories in ASD during the first years of life, previously reported in terms of overall brain volume and surface area.

Early-Life Nutrition and Cognitive Development: Imaging Approaches

Brain development in the first years of life is the most dynamic and perhaps the most important phase of brain maturation. While it is widely recognized that nutrition plays a key role in early brain development, particular nutrients will most likely differentially affect distinct aspects of brain development. The critical dosage windows and time frames for various nutrients at different stages of brain development are likely dissimilar. Therefore, efforts have been devoted to identifying potential associations between nutrients and early brain development. However, behavioral assessments are typically employed as the outcome measures, which are known to suffer from low sensitivity and the inability to provide neural substrates underlying brain functional maturation. In contrast, magnetic resonance imaging is capable of providing detailed anatomical and functional information - an ideal tool to characterize brain functional development and nutrition. Our team has developed strategies that enable imaging of typically developing children from birth to teens without sedation. Quantitative assessments of brain structural and functional development during the first years of life have been accomplished, which reveal important features of early brain development. These developed tools will most likely substantially enhance our ability to rigorously characterize the interplay between nutrients and early brain development.

Infants' gaze exhibits a fractal structure that varies by age and stimulus salience

The development of selective visual attention is critical for effectively engaging with an ever-changing world. Its optimal deployment depends upon interactions between neural, motor, and sensory systems across multiple timescales and neurocognitive loci. Previous work illustrates the spatio-temporal dynamics of these processes in adults, but less is known about this emergent phenomenon early in life. Using data (n = 190; 421 visits) collected between 3 and 35 months of age, we examined the spatio-temporal complexity of young children's gaze patterns as they viewed stimuli varying in semantic salience. Specifically, we used detrended fluctuation analysis (DFA) to quantify the extent to which infants' gaze patterns exhibited scale invariant patterns of nested variability, an organizational feature thought to reflect self-organized and optimally flexible system dynamics that are not overly rigid or random. Results indicated that gaze patterns of even the youngest infants exhibited fractal organization that increased with age. Further, fractal organization was greater when children (a) viewed social stimuli compared to stimuli with degraded social information and (b) when they spontaneously gazed at faces. These findings suggest that selective attention is well-organized in infancy, particularly toward social information, and indicate noteworthy growth in these processes across the first years of life.

Sleep Onset Problems and Subcortical Development in Infants Later Diagnosed With Autism Spectrum Disorder

OBJECTIVE

Sleep patterns in children with autism spectrum disorder (ASD) appear to diverge from typical development in the second or third year of life. Little is known, however, about the occurrence of sleep problems in infants who later develop ASD and possible effects on early brain development. In a longitudinal neuroimaging study of infants at familial high or low risk for ASD, parent-reported sleep onset problems were examined in relation to subcortical brain volumes in the first 2 years of life.

METHODS

A total of 432 infants were included across three study groups: infants at high risk who developed ASD (N=71), infants at high risk who did not develop ASD (N=234), and infants at low risk (N=127). Sleep onset problem scores (derived from an infant temperament measure) were evaluated in relation to longitudinal high-resolution T₁ and T₂ structural imaging data acquired at 6, 12, and 24 months of age.

RESULTS

Sleep onset problems were more common at 6-12 months among infants who later developed ASD. Infant sleep onset problems were related to hippocampal volume trajectories from 6 to 24 months only for infants at high risk who developed ASD. Brain-sleep relationships were specific to the hippocampus; no significant relationships were found with volume trajectories of other subcortical structures examined (the amygdala, caudate, globus pallidus, putamen, and thalamus).

CONCLUSIONS

These findings provide initial evidence that sleep onset problems in the first year of life precede ASD diagnosis and are associated with altered neurodevelopmental trajectories in infants at high familial risk who go on to develop ASD. If replicated, these findings could provide new insights into a potential role of sleep difficulties in the development of ASD.