Latent trajectories of adaptive behaviour in infants at high and low familial risk for autism spectrum disorder

Autism spectrum disorder (ASD) is a set of heterogeneous developmental disorders characterised by difficulties in the social-communication domain, restricted and repetitive patterns of behaviours and interests, and sensory anomalies [1]. A diagnosis of ASD according to the DSM-5 criteria further requires that symptoms cause clinically significant impairments in everyday functioning. The resulting long-term outcome is mixed, but many children diagnosed with ASD will have a suboptimal quality of life in adulthood [2–4], with persisting impairments in everyday functioning [5]. Adaptive behaviour reflects the ability of an individual to function independently in everyday situations and reflects how an individual responds to environmental demands translating capacities into everyday competencies. Evidence suggests that adaptive behaviour in ASD is heterogeneous across individuals and even within the same individual over time [6]. A useful approach to explore this heterogeneity is growth mixture modelling (GMM). GMM is a data-driven approach which allows one to identify distinct mixtures of trajectories within population defining classes of individual growth curves [7]. Previous studies have used GMM to parse samples based on the heterogeneity in the development of adaptive behaviour, mainly focusing on pre-school and school-aged children with ASD [6, 8–11]. These studies analysed approximately 100 children with ASD to derive classes of developmental trajectories on the Adaptive Behaviour Composite (ABC) score [8, 9] and the Daily Living score [10, 11] of the Vineland Adaptive Behavior Scale (VABS-II [12]). Only one study [6] used a larger sample to identify classes in ABC scores (n = 421). Results mainly showed one class with low functioning and decreasing scores, another class with moderate functioning and stable scores over time, and one final class with higher functioning and substantial increase of scores over time. The partial replication of classes across these studies suggests that developmental trajectories of adaptive skills may actually serve to define subgroups in the ASD phenotype.

The work reviewed above focused on children from approximately 3 years of age who already had a diagnosis of ASD. Thus, it could not capture the different developmental trajectories preceding an ASD diagnosis. The investigation of early development of adaptive skills is critical to predict later functional outcome and then enable early targeted intervention. Early access to personalised interventions can, in turn, be crucial to improve later functioning in different environments of everyday life through learning of adaptive skills [13]. This stresses the importance of investigating not only the presence and development of ASD symptoms, which can even be masked by learned strategies to cope with environmental demands [1], but also the different developmental pathways of adaptive behaviour that infants can follow early in life.

However, adaptive behaviour has been rarely used so far as an outcome measure in prospective research. A recent study used mixed models to examine developmental trajectories of cognitive and adaptive functioning between 7 months and 7 years of age, measured respectively by the Mullen Scales of Early Learning (MSEL) and the VABS-II, in infants at familial high-risk (HR) and low-risk (LR) for ASD [14]. Results showed that HR siblings who met the criteria for ASD at age 7 had increasing difficulties in adaptive behaviour over time compared to LR controls, while HR siblings without later ASD outcome did not differ in adaptive behaviour from LR siblings. These findings extend previous work on the same dataset [15] and independent work from Estes and colleagues [16] on trajectories of adaptive behaviour between 8 and 36 months. These studies showed decreased adaptive functioning by 12 months in high-risk siblings developing ASD compared to non-ASD siblings and low-risk controls. There is a partial overlap in data between the study from Salomone et al. [14] and the present study; however, analytic methods and research aims were different. In fact, although these findings improve our understanding of the different developmental profiles of adaptive functioning in infancy and toddlerhood, analyses were based on clinical outcome groups and might not have captured the variation in phenotypes within clinical categories. Only one recent study has investigated latent trajectories of adaptive functioning in a high-risk cohort [17]. This study analysed 566 infants between 12 and 36 months to derive classes of developmental trajectories on the ABC score. Results showed one class with average scores at 12 months and a declining trajectory, one class with a slightly declining trajectory, and one class with higher scores and a stable trajectory.

The current study aimed to identify distinct classes of infants based on the early development of adaptive functioning in HR siblings and LR controls. We used a prospective analysis approach to discover structure in data, independently from clinical categories. Specifically, we used parallel process GMM to simultaneously examine communication, daily living, motor, and social domains of adaptive behaviour, and observe strengths and impairments in the different areas of everyday functioning. Then, we characterised the identified classes in terms of ASD outcome and symptoms at 36 months and concurrent trajectories of cognitive development. Previous studies have shown a discrepancy between adaptive functioning, cognitive abilities, and ASD symptoms in older children with ASD [6, 18–20]. These findings suggest that neither normative cognitive development nor low levels of ASD symptoms are protective factors against poor adaptive functioning. Our post hoc association of class membership with cognitive development and symptom severity allowed us to investigate the relationship between these three areas of functioning in early development. Overall, the exploratory investigation of inter-individual heterogeneity with such an unsupervised approach provides better insight into the variety of paths leading to different functional outcomes within ASD and typical development.

Three classes of quadratic trajectories provided the best fit to the data, with BIC = 28,523.12 and AIC = 28,397.82 and average posterior probability of 87%. Metrics of model fitting are reported in Additional file 1: Table S2. The identified trajectories of adaptive behaviour are shown in Fig. 1. Modelling the corresponding trajectories in ELC scores (Fig. 2), the quadratic model was the best fit for the data (χ² [6] = 26.2, p < 0.001).

This figure illustrates the developmental trajectories of cognitive level, as measured by the ELC score from the Mullen Scales of Early Learning, for the three classes identified in longitudinal adaptive behaviour. Points show individual scores while classes were computed through the loess function in R for visualisation purposes. Class 1 shows a decreasing trajectory in cognitive level; classes 2 and 3 show stable trajectories at an average level of cognitive development.]

Class 1 (n₁ = 20 (8.3%)) shows decreasing trajectories in all domains of adaptive behaviour (fixed effect of age in the common longitudinal model: β = − 0.27, standard error (SE) = 0.08, p = 0.001) starting with above average age-standardised scores in communication, daily living, and socialisation skills and average scores in motor skills in the first year of life. This is the only class with unbalanced gender, being more males (65%) than females (35%). Results from linear mixed modelling show that infants in class 1 had significantly decreasing standardised scores in communication, daily living, and socialisation domains between 8 and 24 months (p < 0.001), and in socialisation between 24 and 36 months (p = 0.04), while motor scores decreased significantly only between 14 and 24 months (p = 0.02). Infants in this class also show a similar trajectory in cognitive development over time, with decreasing ELC scores before age 2 (p < 0.001), starting from above average scores in the first year of life.

Class 2 (n₂ = 177 (73.8%)) shows stable trajectories around average scores in all domains of adaptive behaviour (fixed effect of age in the common longitudinal model: β = 0.11, SE = 0.03, p < 0.001). Gender was balanced in this class, with 48% of males and 52% of females. Results from linear mixed modelling show that infants had significantly increasing age-standardised scores between 8 and 14 months in communication (p = 0.004) and daily living domains (p = 0.04); increasing scores between 14 and 24 months in communication, daily living, and motor domains (p < 0.001); and decreasing motor scores between 24 and 36 months (p < 0.001). Infants in this class show a stable trajectory around average scores in cognitive development before age 2 and increasing ELC scores afterwards (p = 0.005).

Class 3 (n₃ = 43 (17.9%)) shows recovering (improving) trajectories (fixed effect of age in the common longitudinal model: β = 0.43, SE = 0.10, p < 0.001) starting from low scores and reaching a stable average level in all domains by age 2. Gender was balanced in this class, with 47% of males and 53% of females. Results from linear mixed modelling show that infants had significantly increasing age-standardised scores between 8 and 24 months in all domains of adaptive behaviour (p < 0.001). Infants in this class also show a stable trajectory around average scores in cognitive development before age 2 with increasing ELC scores afterwards (p = 0.007).

Mixed models on trajectories of adaptive behaviour show that class 3 had significantly lower scores than classes 1 and 2 in all domains at 8 months (p < 0.001), while it had only significantly lower scores than class 2 in communication and motor scores at 14 months (p < 0.001). Class 1 had significantly lower scores than classes 2 and 3 in communication (p < 0.001), daily living (p = 0.002 and p = 0.006, respectively), motor (p = 0.004 and p < 0.05, respectively), and socialisation scores (p = 0.006 and p = 0.002, respectively) at 24 months. Finally, class 1 had significantly lower scores than classes 1 and 2 in communication (p < 0.001), daily living (p < 0.001), motor (p = 0.002 and p = 0.007, respectively), and socialisation scores (p < 0.001) at 36 months (see Fig. 1).

This study explored latent trajectories of adaptive functioning in infants at high and low familial risk for ASD. We observed variability in the development of adaptive functioning before age 2 and found three latent classes: one class with scores at or above age-appropriate norms at the first visit but decreasing trajectories afterwards (class 1), one class with a relatively stable trajectory around age-appropriate norms (class 2), and one class with increasing scores from below age-appropriate norms before age 2 to stable average scores afterwards (class 3). Thus, high adaptive skills early in development were counterintuitively associated with poorer adaptive functioning in toddlerhood, while an initially delayed development appeared to be recovered by age 2. From age 2 onwards, the identified classes mainly showed one relatively stable trajectory around average scores and a below-average decreasing trajectory, consistent with previous findings on older children with ASD [6, 8, 9]. Of note, classes significantly differed in ASD symptom severity and clinical outcome. Infants in class 1 had significantly higher symptom severity at 36 months, and there were more siblings who later met the criteria for ASD than expected by a randomly distributed ASD outcome. Another important finding was a partial split between adaptive behaviour and cognitive development of the identified classes. In fact, class 3 showed a stable trajectory around average cognitive level while it was identified by improving adaptive behaviour before age 2 and a stable trajectory around average scores afterwards.

Classes did not clearly map to clinical outcome groups. In our sample, 68% of infants developing ASD showed rather stable trajectories of adaptive skills around age-appropriate norms (class 2), 23% of them showed decreasing skills (class 1), and only 9% of them showed recovering adaptive skills by age 2 (class 3). Similarly, the HR-Atypical outcome group was spread over the three classes, although the majority was in class 2. This provides further support to the high heterogeneity of ASD in its phenotypic manifestations [34–36]. Yet, it is in contrast with our previous work on group comparisons, showing significantly lower adaptive skills in HR-ASD siblings compared to HR-Typical or LR controls and overall stable-low or decreasing trajectories of adaptive behaviour in infancy [14, 15]. However, our approach here is focused on the identification of latent classes of trajectories independently from diagnostic outcome. Such approach allowed us to explore individual differences in early development and to identify different profiles within the ASD group.

Different trajectories of adaptive behaviour did not correspond to significant differences in ADOS scores, but there were significant differences in ADI-R and SCQ scores. This extends to infancy previous findings on discrepancies between adaptive behaviour and ADOS scores in pre-schoolers with ASD [6]. However, not all ASD symptoms are captured by the ADOS, and some children with “atypical” outcomes had by definition high ADOS scores (but did not meet diagnostic criteria for ASD). Rather, the relationship between adaptive behaviour and symptom severity can be captured by investigating all the instruments employed to assess symptom severity at 36 months (i.e. ADOS, ADI-R, and SCQ). The split between ADI-R/SCQ and ADOS might be due to the parent-reported nature of ADI-R and SCQ scores, the same as VABS scores used to identify classes of infants, while ADOS scores are based on clinical observations.

It is remarkable to observe initially average or above-average adaptive functioning in some infants with later ASD outcome (class 1). Nevertheless, they also showed a decreasing trajectory of scores compared to age-appropriate norms over time, which is in line with previous findings on children with ASD [6, 8]. Furthermore, the timing of the decline observed here is consistent with the emergence of overt behavioural signs of ASD as generally observed in previous studies around the second year of life [37–39]. Thus, an initial high level of adaptive functioning seems not to prevent ASD development; rather, when followed by a decline over time, it seems to be associated with a higher likelihood of ASD in toddlerhood. However, given that class 1 represents only 7% of infants in our sample, we must be cautious with interpretations. Our findings are somewhat similar to what is observed in neuroimaging studies. There, higher fractional anisotropy and volume in the development of fibre tracts [40, 41], accelerated expansion of cortical surface area, and brain volume overgrowth [42] in the first year of life were linked to later ASD outcome. One may speculate that high levels of adaptive skills early in development are linked to early alterations of brain development. In particular, hyper-expansion of cortical surface area may compromise the development of proper neural connectivity [43] and have downstream effects on behaviour, leading to the emergence of symptoms characteristic of ASD in toddlerhood. A recent framework for neurodevelopmental disorders suggests, in fact, that good synaptic compensation to overcome initial impairment at an earlier developmental stage might have more severe consequences later in development [44]. The declining trajectory of adaptive skills that we observed likely reflects little gain of skills between the first and second year of life and a failure to keep up with development. Further research should integrate more biological data on brain structure and brain function, such as EEG or MRI, to investigate what could have triggered the plateauing of skills for infants in class 1. This would also provide more insight into the biological mechanisms underlying the identified developmental trajectories. Furthermore, while classes 2 and 3 were balanced in gender, class 1 was mostly composed by males. This is consistent with the gender bias in the prevalence of ASD [45] and with previous findings in children with ASD showing higher daily living scores in females than males [46]. Overall, this suggests that sex might moderate how clinical symptoms are expressed in adaptive behaviour.

In terms of developmental level, the three classes of adaptive functioning correspond to the two main classes of cognitive development. Infants falling behind age-appropriate norms in adaptive behaviour (class 1) also showed decreasing trajectories in cognitive development, with significantly lower scores compared to their peers by age 2. On the other hand, infants with stable or improving adaptive behaviour (classes 2 and 3) did not differ in terms of developmental level, showing rather stable trajectories around age-appropriate norms. Discrepancy between adaptive and cognitive skills has been found before [14, 47], showing lower and more divergent adaptive skills compared to cognitive level. Our findings suggest that the main differences between decreasing and stable/increasing trajectories in adaptive behaviour might be driven by the differences in cognitive level. Less cognitively able individuals appear to fall behind age-appropriate norms in adaptive behaviour, while more cognitively able individuals show stable or increasing trajectories of adaptive behaviour around age-appropriate norms. Cognitive impairment has been shown to have a negative effect on everyday functioning and the development of adaptive behaviour, even beyond the effect of ASD symptoms [19]. However, the profile of good cognitive abilities with poor adaptive skills, which has been reported before in older children with ASD [18, 20], has not emerged from our study. Such profile might emerge later in life, as we have found in a follow-up of part of the current sample in mid-childhood [14]. This highlights the complexity of the development of adaptive behaviour and its relationship with cognitive development and ASD symptomatology, suggesting the necessity to further investigate adaptive behaviour in infancy.

Although findings are consistent, our study differs in three ways from the recent study of Sacrey et al. [17] on latent trajectories of adaptive behaviour in infancy. First, we identified classes across domains of adaptive behaviour instead of ABC score alone, providing more detailed profiles. Second, we used growth mixture modelling [7] instead of latent class growth curve modelling [29], allowing variation within class to capture heterogeneity across individuals. Third, we examined younger ages by including data at 8 months. This earlier observation added particular value to our findings. In fact, children who later met the criteria for ASD might not simply follow a trajectory of progressive impairment in adaptive skills, but some of them might present even stronger skills in the first year of life compared to other subgroups of infants. Our study has strengths in the relatively large sample of infant siblings (n = 240) and the analysis of multiple instruments (MSEL, VABS, ADOS, ADI-R, and SCQ), but it also has limitations. First, although trajectories were separated at the group level, there was still a substantial overlap between classes in individual variation. Second, the three-step approach we used to examine the association of class membership with external variables might underestimate such relationship [48]. This is particularly true when classification errors in the assignment of individual class membership are high, and it might explain the discrepancy between VABS, MSEL, and ADOS found in our study. However, high average class posterior probability was a selection criterion for the best model, reducing the impact of classification errors. Third, adaptive behaviour was assessed on the basis of parent-reported measures; however, class comparisons in terms of cognitive level and symptom severity, assessed by observational measures, enhance our confidence in the identified trajectories. Fourth, follow-up studies should investigate trajectories on a higher number of time-points to improve the estimate of the shape of the trajectory curve and test whether they change at later age. Finally, experimenters’ awareness of risk-group status might lead to ascertainment bias due to more intense surveillance for ASD outcome among high-risk siblings compared to low-risk controls.

High-risk siblings and low-risk controls could be separated into three latent classes representing declining, improving, and stable trajectories of adaptive behaviour between 8 and 36 months. We observed a dissociation between adaptive behaviour and cognitive development, with the improving class in adaptive behaviour showing stable trajectories of cognitive development around average scores. Furthermore, classes significantly differed in ASD symptoms and clinical outcome at 36 months. High levels of adaptive functioning in the first year of life followed by a failure to keep up with age-appropriate norms were linked to higher symptom severity across the social, communication, and repetitive behaviours domains. Furthermore, it was linked to increased likelihood of meeting diagnostic criteria for ASD in toddlerhood. Our findings provide better insight into the variety of paths leading to different functional outcomes within ASD. The identified subgroups indicate homogeneous classes of infants in terms of progression of adaptive functioning over time. These subgroups might be more relevant target groups for intervention aimed at improving later functioning.