Association of Sex with Neurobehavioral Markers of Executive Function in 2-Year-Olds at High and Low Likelihood of Autism

Importance: Children with autism and their siblings exhibit executive function (EF) deficits early in development, but associations between EF and biological sex or early brain alterations in this population are largely unexplored. Objective: To investigate the interaction of sex, autism likelihood group, and structural magnetic resonance imaging alterations on EF in 2-year-old children at high familial likelihood (HL) and low familial likelihood (LL) of autism, based on having an older sibling with autism or no family history of autism in first-degree relatives. Design, Setting, and Participants: This prospective cohort study assessed 165 toddlers at HL (n = 110) and LL (n = 55) of autism at 4 university-based research centers. Data were collected from January 1, 2007, to December 31, 2013, and analyzed between August 2021 and June 2022 as part of the Infant Brain Imaging Study. Main Outcomes and Measures: Direct assessments of EF and acquired structural magnetic resonance imaging were performed to determine frontal lobe, parietal lobe, and total cerebral brain volume. Results: A total of 165 toddlers (mean [SD] age, 24.61 [0.95] months; 90 [54%] male, 137 [83%] White) at HL for autism (n = 110; 17 diagnosed with ASD) and LL for autism (n = 55) were studied. The toddlers at HL for autism scored lower than the toddlers at LL for autism on EF tests regardless of sex (mean [SE] B = -8.77 [4.21]; 95% CI, -17.09 to -0.45; η2p= 0.03). With the exclusion of toddlers with autism, no group (HL vs LL) difference in EF was found in boys (mean [SE] difference, -7.18 [4.26]; 95% CI, 1.24-15.59), but EF was lower in HL girls than LL girls (mean [SE] difference, -9.75 [4.34]; 95% CI, -18.32 to -1.18). Brain-behavior associations were examined, controlling for overall cerebral volume and developmental level. Sex differences in EF-frontal (B [SE] = 16.51 [7.43]; 95% CI, 1.36-31.67; η2p= 0.14) and EF-parietal (B [SE] = 17.68 [6.99]; 95% CI, 3.43-31.94; η2p= 0.17) associations were found in the LL group but not the HL group (EF-frontal: B [SE] = -1.36 [3.87]; 95% CI, -9.07 to 6.35; η2p= 0.00; EF-parietal: B [SE] = -2.81 [4.09]; 95% CI, -10.96 to 5.34; η2p= 0.01). Autism likelihood group differences in EF-frontal (B [SE] = -9.93 [4.88]; 95% CI, -19.73 to -0.12; η2p= 0.08) and EF-parietal (B [SE] = -15.44 [5.18]; 95% CI, -25.86 to -5.02; η2p= 0.16) associations were found in girls not boys (EF-frontal: B [SE] = 6.51 [5.88]; 95% CI, -5.26 to 18.27; η2p= 0.02; EF-parietal: B [SE] = 4.18 [5.48]; 95% CI, -6.78 to 15.15; η2p= 0.01). Conclusions and Relevance: This cohort study of toddlers at HL and LL of autism suggests that there is an association between sex and EF and that brain-behavior associations in EF may be altered in children at HL of autism. Furthermore, EF deficits may aggregate in families, particularly in girls

An analysis-ready and quality controlled resource for pediatric brain white-matter research

We created a set of resources to enable research based on openly-available diffusion MRI (dMRI) data from the Healthy Brain Network (HBN) study. First, we curated the HBN dMRI data (N = 2747) into the Brain Imaging Data Structure and preprocessed it according to best-practices, including denoising and correcting for motion effects, susceptibility-related distortions, and eddy currents. Preprocessed, analysis-ready data was made openly available. Data quality plays a key role in the analysis of dMRI. To optimize QC and scale it to this large dataset, we trained a neural network through the combination of a small data subset scored by experts and a larger set scored by community scientists. The network performs QC highly concordant with that of experts on a held out set (ROC-AUC = 0.947). A further analysis of the neural network demonstrates that it relies on image features with relevance to QC. Altogether, this work both delivers resources to advance transdiagnostic research in brain connectivity and pediatric mental health, and establishes a novel paradigm for automated QC of large datasets

What’s retinoic acid got to do with it? Retinoic acid regulation of the neural crest in craniofacial and ocular development

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151310/1/dvg23308.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151310/2/dvg23308_am.pd

Integration of modern data management practice with scientific workflows

F1 - Full Written Papers Referee