![]() ![]() Accordingly, we now describe the longitudinal trajectory and the stability of IQ scores in this ASD sample compared to age-matched, typically developing controls (TDC). In the ISLA study, participants were enrolled as young as 3 years of age and have been tracked to the current time frame some participants have been followed and re-examined for more than 22 years with up to 7 time points of IQ data. Research has shown that adult outcome is poor to very poor in up to 60% of individuals in this subgroup (Howlin et al., 2013). To date, the project has focused on the subgroup of individuals with autism whose cognitive ability (nonverbal IQ) is ≥ 70. ![]() The goal of ISLA is to understand central tendencies, variation in brain development and maturation and the relationship to variation in clinical course and adult outcome. The longitudinal Interdisciplinary Science to Learn about Autism (ISLA) project is an NIH-funded study of how clinical phenotypes and multimodal brain images change over time in ASD individuals. Additional waves of data, of 3 time points or more, add to the measurement of individual trajectories and reliability of estimated change at the group level by statistical regression models (Willett et al., 1998). To date, limitations of longitudinal ASD studies of IQ across the lifespan include lack of a control sample, estimates of IQ scores from adaptive functioning, and most importantly, a limited number of time points per individual (≤ 3) from which to infer longitudinal change or stability. Some studies have shown a decline in IQ in 23–35% of the participants, while 18–33% of the participants show an increase in IQ scores from childhood to adulthood (Farley et al., 2009 Howlin et al., 2014). The few studies that have tested ASD participants in childhood and repeated testing in young adulthood report an overall gain of 7 points (Simonoff et al., 2019) and significant variability (Bishop et al., 2015 Lord et al., 2015). Longitudinal childhood studies show that some ASD participants have stable IQ scores (within ± 1 SD), yet many individuals have scores that increase or decrease over time (see Begovac et al., 2009 for a review Solomon et al., 2018). ![]() Cross-sectional studies have examined IQ in those with ASD from childhood to adulthood (Charman et al., 2017 Tillmann et al., 2019) but do not inform on individual changes. A better understanding of the IQ metric as assessed in individuals with ASD has broad implications for all facets of the condition.ĭespite the importance of the IQ measure in the clinical care of individuals with ASD and in ASD research, very little is known about the stability of IQ longitudinally, especially during the transitions from childhood through adolescence and into adulthood (Martos-Perez et al., 2018). Because a modest but positive correlation exists between IQ and regional brain volumes (Lange et al., 2010) and cortical thickness (Zielinski et al., 2014), psychometric computation of IQ scores has become an important matching and/or statistical control feature in neuroimaging research (Bigler, 2017). A general intelligence factor, “g”, is thought to mediate the interrelationships between all cognitive processes and IQ (Deary, 2012). Psychometrically, IQ correlates positively with essentially all other cognitive metrics, particularly language and memory (Prigge et al., 2013 Southwick et al., 2011). Lower levels of intellectual functioning have been associated with higher levels of ASD symptom severity (Bishop et al., 2006 Charman et al., 2017 Mayes et al., 2011 Nordin & Gillberg, 1998) and are one of the strongest childhood predictors of diagnostic and functional outcome in adulthood (D. Basic relations exist between level of intellectual functioning and social processing (Bishop-Fitzpatrick et al., 2017 Morrison et al., 2019) this relationship is a problematic area of cognitive processing and adaptive functioning in those with ASD (Kraper et al., 2017). Tests of intelligence, most commonly assessed as intelligence quotients (IQ) metrics or index scores, are typically obtained on all individuals who meet criteria for ASD because of the major implications for educational, vocational, and treatment planning and understanding vulnerability to distressing emotional states (Kraper et al., 2017 Mayes & Calhoun, 2003 Mayes et al., 2011 Pallathra et al., 2018 Solomon et al., 2018 Stewart et al., 2017 Tureck et al., 2014). Measures of intelligence are important in the clinical evaluation of children and adults with Autism Spectrum Disorder (ASD) and in ASD research. ![]()
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