Brain functional connectivity correlates of autism diagnosis and familial liability in 24-month-olds.

Researchers studied brain scans of 2-year-olds to understand autism and family risk factors. They found that children with an older autistic sibling showed different brain connectivity patterns compared to children without family history of autism. Importantly, these brain differences were present whether or not the younger sibling was diagnosed with autism, suggesting that genetic risk factors affect brain development even when autism isn't diagnosed.

This neuroimaging study examined brain connectivity patterns in 24-month-old toddlers to understand autism diagnosis and familial risk. Researchers compared children with high familial likelihood (older autistic sibling) who were either diagnosed with ASD (HLP, n=23) or not (HLN, n=91), against low-likelihood controls (LLN, n=27). Machine learning algorithms achieved 99% accuracy distinguishing HLP from HLN groups based on widespread brain connectivity differences. Both high-likelihood groups showed reduced connectivity in default mode networks compared to controls, suggesting this pattern relates to familial autism liability rather than diagnosis alone.

The findings indicate that brain connectivity alterations may be present in children at genetic risk for autism, regardless of whether they receive a diagnosis.

Findings suggest brain connectivity patterns may serve as early biomarkers for autism risk in families with genetic liability. However, clinical application requires further validation and longitudinal studies to determine predictive value for developmental outcomes.

Study used complex neuroimaging analysis methods that require validation. Sample size for autism-diagnosed group was relatively small (n=23). Cross-sectional design prevents understanding of how these brain patterns develop over time or predict outcomes.

fcMRI correlates of autism spectrum disorder (ASD) diagnosis and familial liability were studied in 24-month-olds at high (older affected sibling) and low familial likelihood for ASD. fcMRI comparisons of high-familial-likelihood (HL) ASD-positive (HLP, N = 23) and ASD-negative (HLN, N = 91), and low-likelihood ASD-negative (LLN, N = 27) 24-month-olds from the Infant Brain Imaging Study (IBIS) Network were conducted, employing object oriented data analysis (OODA), support vector machine (SVM) classification, and network-level fcMRI enrichment analyses. OODA (alpha = 0.0167, 3 comparisons) revealed differences in HLP and LLN fcMRI matrices (p = 0.012), but none for HLP versus HLN (p = 0.047) nor HLN versus LLN (p = 0.225). SVM distinguished HLP from HLN (accuracy = 99%, PPV = 96%, NPV = 100%), based on connectivity involving many networks. SVM accurately classified (non-training) LLN subjects with 100% accuracy.

Enrichment analyses identified a cross-group fcMRI difference in the posterior cingulate default mode network 1 (pcDMN1)- temporal default mode network (tDMN) pair (p = 0.0070). Functional connectivity for implicated connections in these networks was consistently lower in HLP and HLN than in LLN (p = 0.0461 and 0.0004). HLP did not differ from HLN (p = 0.2254). Secondary testing showed HL children with low ASD behaviors still differed from LLN (p = 0.0036). 24-month-old high-familial-likelihood infants show reduced intra-DMN connectivity, a potential neural finding related to familial liability, while widely distributed functional connections correlate with ASD diagnosis.