Autism spectrum disorder (ASD) is a highly heritable (
1) neurodevelopmental disorder diagnosed in 1 in 54 children in the United States (
2). Younger siblings of children with ASD have a higher likelihood of developing ASD, where 1 in 5 siblings followed from infancy will receive a diagnosis of ASD by 3 years of age (
3). Prospective MRI and behavioral studies of infant siblings have revealed that brain changes in ASD precede the onset of core diagnostic features and are temporally associated with behavioral changes that emerge in the latter part of the first and second years of life (
4). Aberrant white matter integrity (
5), altered morphology of the corpus callosum (
6), and increased extra-axial CSF volumes (
7,
8) are detectable as early as 6 months of age in infants who go on to develop ASD. Cortical surface area hyperexpansion from 6 to 12 months, particularly in regions in the occipital cortex, precedes and is correlated with brain volume overgrowth from 12 to 24 months (
9), coinciding with the emergence and consolidation of ASD symptoms in the second year. Brain features, and in particular regional surface area, measured from MRIs taken in the first year of life predicted the later diagnosis of ASD in toddlerhood (
9). Less is known about functional brain development in early autism, and no functional connectivity MRI (fcMRI) studies to date have demonstrated group differences in connectivity patterns between infants who develop ASD and infants who do not. However, a subset of behavior-related 6-month region-to-region connections has been shown to accurately predict diagnostic outcome at 24 months of age in infant siblings (
10). To date, brain imaging markers from the first year of life remain some of the strongest predictors of later ASD diagnosis among infants (
11).
While it is evident that brain development is atypical in infants who are later diagnosed with ASD, the link between brain maturation and inherited genetic factors is unclear. Common polygenic variation accounts for the majority of genetic liability for autism (
12), especially in multiplex families where more than one child has an ASD diagnosis (
13), although the current predictive utility of molecular genetic markers of polygenic liability for ASD is limited (
14). In the context of the infant sibling study design, family traits may serve as useful, cost-effective early markers of inherited genetic liability for autism. Autistic traits aggregate in families and are heritable (
15–
19), with numerous studies reporting higher likelihood for recurrence (
3,
20) and greater levels of ASD traits (
21,
22) in multiplex families relative to single-incidence (simplex) families. In line with this work, we previously reported that elevated levels of autistic traits in older ASD siblings (probands) increase the likelihood of an ASD diagnosis in younger siblings (
23). Linking family traits to individual variation in early brain imaging markers of autism in infants has important implications for both etiology and prediction. If family traits account for significant variation in infant brain development, this would not only identify which brain phenotypes track with familial liability for ASD and warrant further molecular genetic dissection and mechanistic study, but it could also yield insight into individualized areas of concern relevant to early intervention. This type of family-design approach has already exhibited great promise for predicting clinical severity in rare genetic disorders affecting brain development (
24,
25).
To address the gap in our understanding of how inherited liability for ASD impacts infant brain development, we tested whether autistic traits in ASD probands explain variation in ASD-associated brain phenotypes in their younger siblings during the period preceding and coinciding with the onset of symptoms. First, we examined whether probands’ autistic traits were associated with brain phenotypes in their younger siblings that have been shown to differ in infants later diagnosed with ASD with independent laboratory/cohort replication: cerebral volume (
7,
9), cortical surface area (
9,
26), and extra-axial CSF (
7,
8). We hypothesized that higher levels of ASD traits in probands—indicative of increased genetic liability for ASD (
23)—would be associated with larger brain volume, cortical surface area, and extra-axial CSF volumes in siblings. Next, we took a targeted approach to study occipital cortical surface area and splenium white matter microstructure, based on evidence that 1) occipital cortical regions have been shown to exhibit hyperexpansion during infancy in infants who develop ASD (
9) and 2) splenium microstructure at 6 months of age predicts autism diagnosis at 24 months (
27) and has been implicated in the development of visual orienting, a behavior that is aberrant as early as 6 months of age in infants who later develop ASD (
28). Given that these global and regional brain phenotypes have been shown to differ in ASD and control subjects, we were also interested in whether proband traits may have differential associations with brain development in siblings later diagnosed with ASD compared with those without a diagnosis. Finally, results from analyses of occipital surface area and splenium microstructure led us to investigate associations between proband ASD traits and functional connectivity during infancy. The findings reported here provide evidence that specific early brain phenotypes of ASD reflect quantitative variation in familial ASD traits, revealing insights into the developmental nature of gene-brain associations in autism during the presymptomatic period leading up to diagnosis.
Discussion
We utilized a family-study design to demonstrate that autistic traits in ASD probands, as indices of familial genetic liability for ASD, correlate with neurodevelopment in the probands’ infant siblings who were later diagnosed with ASD. Proband autism traits—and, in particular, social behavior captured by multiple instruments—explained variation in sibling cerebral volume, cortical surface area, and splenium white matter microstructure during the presymptomatic period leading up to diagnosis. Our structural and diffusion MRI findings included cortical regions and fiber pathways involved in processing visual information at 6 months of age, and were consistent with our fcMRI enrichment results, demonstrating convergence across multiple imaging modalities. Together, these findings suggest a role for heritable ASD liability in shaping the development of visual circuitry during infancy when aberrant visual behaviors in autism are evident. The results also indicate that ASD traits in older siblings may foreshadow the emergence of ASD in their younger siblings and may be useful as markers of family-level liability.
Brain volume overgrowth is well documented in ASD and becomes apparent in the second year of life, following the hyperexpansion of cortical surface area (
9). Common ASD genetic variants are predicted to regulate corticogenesis (
14), and gene expression profiles in postmortem cortico-cortical projection neurons have been found to correlate with symptom severity in ASD (
52). Our findings build on this work to link familial indices of genetic liability with variations in the early postnatal development of cerebral volume and cortical surface area, suggesting that autistic traits in families may serve as markers for ASD-associated brain overgrowth in infants.
Regional analyses revealed that greater levels of autism traits in probands were associated with larger surface area in a subset of cortical areas that exhibit hyperexpansion and contribute to individual-level diagnostic prediction in infants who develop ASD (
9). Distinct sets of genes are involved in the development of specific cortical regions in humans, with strong genetic correlations for surface area among occipital cortical regions surrounding major early-forming sulci (
53). Canonical Wnt signaling, which has been implicated in the pathophysiology of ASD (
54), modulates regional surface area with functional links to genes involved in Wnt signaling enriched in occipital cortical areas (
53). This aligns with our finding that surface area in the occipital cortex is associated with proband traits that index genetic liability for ASD, implicating mechanisms governing occipital cortical areal expansion in the pathophysiology of ASD.
Unlike brain volume and surface area, we found no associations between proband traits and sibling extra-axial CSF volumes. Previous reports indicate that extra-axial CSF volumes are increased in toddlers with ASD regardless of familial liability (
55), and thus extra-axial CSF may represent a nonspecific marker of vulnerability to atypical neurodevelopment. Our family-study paradigm may help to identify brain phenotypes most strongly linked to inherited polygenic variants (cortical volume, surface area) versus those that may arise through a separate pathophysiology (extra-axial CSF).
Proband ASD traits explained 20% of the variance in splenium microstructure at 6 months of age, but not at 12 or 24 months, such that greater levels of proband ASD traits were associated with an age-specific increase in FA in ASD siblings. This is consistent with evidence that infants who develop ASD have higher values of FA at 6 months of age in white matter tracts spanning the brain, followed by a period of slowed growth and ultimately lower FA at 24 months of age (
5). Our results suggest that initially higher FA in ASD siblings—reflective of an overabundance of axons, increased myelination, or both—are driven by genetic liability for autism, but that the slower maturation of white matter FA thereafter may be modified to a greater degree by experience-dependent mechanisms.
Greater levels of autism traits in probands were associated with weaker connectivity between the pDMN and Vis networks, the pDMN and mVis networks, and the pFP and Vis networks at 6 months of age in siblings, suggesting that greater familial genetic liability for ASD confers weaker functional connectivity between visual and DMN regions and between visual and task-control regions. Weaker connectivity between DMN and visual networks has been linked to initiating fewer bids for joint attention in our sample (
38) and has been observed in ASD toddlers with deficits in visual-social engagement (
56). Differences in the interhemispheric connectivity of the posterior cingulate cortex (a hub of the DMN) and extrastriate cortex have also recently been reported among infant siblings of ASD probands at 9 months of age compared with control infants without a family history of ASD (
51). These results align with our findings linking proband traits to other components of the visual system, including the middle occipital gyrus, which lies along the dorsal stream (
57) and is involved in the processing of visual information, including object recognition (
58,
59), and the splenium, which is critical for interhemispheric communication between visual areas (
60) and has been shown to reflect visual orienting latencies in infants (
28).
Together, these results suggest that genetic liability for autism plays a role in shaping the development of neural circuitry relevant for visual processing at 6 months of age, prior to the emergence of the defining behavioral features of ASD. Eye-looking and gaze behavior (
61), viewing of social scenes (
62), and visual orienting (
28) are aberrant during infancy and toddlerhood in ASD. Patterns of visual preference to social stimuli (e.g., eyes, mouth) during infancy are under strong genetic control (
62), suggesting that genetic background may play a pivotal role in shaping infants’ experience of the environment around them, generating a dynamic gene-environment developmental system for social learning (
63). Thus, we posit that the early, atypical structure and function of visual circuitry related to a genetic predisposition for autism may initiate a developmental cascade whereby altered visual circuitry subserves atypical visually guided behaviors, which in turn shapes visual experience and experience-dependent circuit refinement and contributes to the emergence of the defining symptoms of ASD (
4).
Findings linking proband ASD traits to sibling structural and diffusion brain imaging phenotypes were specific to the ASD group and were not observed in the non-ASD group. The association between proband traits and sibling brain phenotypes is indicative of a shared genetic liability among sibling pairs who develop ASD, while the lack of associations in non-ASD siblings could be explained by nonshared genetics, phenotypic heterogeneity (
64), or both. These hypotheses will need to be tested through genetic investigation. It also warrants mention that the SCQ was designed to capture trait variation at the diagnostic end of the continuum, and therefore may not index characteristics that are qualitatively similar but milder than those seen in the diagnostic category of ASD that are known to aggregate in first-degree relatives without a diagnosis (e.g., non-ASD siblings). Finally, using the ADI-R, we found that proband symptoms in the social domain appear to be more strongly associated with ASD sibling brain development than restricted and repetitive behaviors. This aligns with evidence that social and nonsocial domains of autism symptomatology are both heritable (
19) and genetically dissociable (
65), suggesting that their underlying genetic architecture may have different impacts on the developing brain.
There are limitations of this study. Familial autistic traits are not direct measures of the genetic architecture of ASD and likely capture some degree of environmental influences; future studies should seek to expand these findings to molecular genetic investigations (i.e., polygenic risk scores) that may have more relevance for early brain development. Limited sample sizes prevented us from testing for diagnostic group interactions with proband traits in the fcMRI enrichment analyses; we were unable to determine whether the associations between proband trait level and fcMRI were driven by the ASD group (as was the case with the structural and diffusion findings) or were similar in nature across the entire sample. Finally, the published work identifying regions in the occipital lobe (
9) and the splenium (
27,
28) as phenotypes of interest drew from the same cohort of infants reported on here, and thus the specificity of findings to these brain areas could be influenced by cohort-specific effects. The ongoing collection of another infant cohort will help to address sample size concerns in future investigations and allow for studies seeking to replicate findings from this study and much of our prior work identifying brain biomarkers in emerging ASD. It will be critical to determine whether these findings generalize to other infant cohorts.
These limitations notwithstanding, the results from this study provide a proof-of-principle for utilizing heritable, familial autistic traits to identify neural signatures of ASD that may be impacted by genetic liability prior to the onset of symptoms. This sets the stage for parsing phenotypic heterogeneity and polygenicity of idiopathic autism by mapping genes to neural signatures, or endophenotypes, of ASD that may more closely reflect the underlying biology. Large-scale imaging genetics studies have demonstrated that common genetic variation is more strongly associated with brain structure than categorical neuropsychiatric diagnosis, and that brain imaging phenotypes show reduced polygenicity and increased discoverability relative to diagnostic categories (
66). It follows that by focusing efforts on gene discovery using phenotypes such as visual cortical surface area during infancy, for example, we reduce the search space for possible underlying pathogenic processes, ultimately accelerating the discovery of causal mechanisms and therapeutic targets. Coupling such a methodological approach with detailed longitudinal investigation in human infants has great potential to inform our understanding of the links between polygenic variants, brain development, and behavior during a period when autistic symptoms are first unfolding. Targeting studies to the early postnatal period is likely to be critical, as growing evidence suggests that clinical symptomology after onset may be more driven by environmental and stochastic effects, blurring the line between initial genetic pathogenic mechanisms and cumulative changes in the environment, or one’s experience of the environment, that may subsequently shape clinical presentation.