Age-Dependent Alterations in Resting State Connectivity in the Broader Autism Phenotype - a Twin Study

Saturday, May 13, 2017: 1:39 PM
Yerba Buena 9 (Marriott Marquis Hotel)
J. Neufeld1, P. Fransson2, R. Kuja-Halkola3, E. Cauvet1, K. Mevel4 and S. Bolte1, (1)Center of Neurodevelopmental Disorders at Karolinska Institutet (KIND), Institutionen för kvinnors och barns hälsa (KBH), Karolinska Institutet, Stockholm, Sweden, (2)Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden, (3)Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, (4)Laboratory for the Psychology of Child Development and Education (LaPsyDÉ), CNRS UMR 8240, Sorbonne Paris Cité, GIP Cyceron, Université de Caen Normandie, Université Paris Descartes, Paris, France, Paris, France
Background: Altered functional brain connectivity during the resting state (RS) has commonly been reported in individuals diagnosed with Autism Spectrum Condition (ASC). However, findings are largely inconsistent, showing both increased and decreased connectivity in various regions. Insufficient control for confounding factors, such as genetic and environmental influences, but also head motion during brain scanning (Power et al., 2012), potentially lead to biased results. Further, recent studies suggest that altered connectivity in ASC compared to typically developing (TD) individuals might be age-dependent (Nomi & Uddin, 2015; Dajani & Uddin 2015; Alaerts et al., 2015) while only few studies tested age-effects.

Objectives: The current study aims to specifically test connectivity within two RS networks commonly reported to be altered in ASC: the Default Mode Network (DMN) and the Salience Network (SN). In order to gain more conclusive results 1) a marked reduction of confounding is achieved using a twin design (Mevel et al., 2014) while 2) carefully controlling for head motion. Further, 3) in accordance with the Research Domain Criteria (RDoC) we focus on dimensional rather than categorical outcomes (Insel et al., 2010) and 4) stratification by age is applied in order to detect age-specific differences.

Methods: Monozygotic (MZ) and dizygotic (DZ) twins (N=150, 61.3%MZ; 64%male, age:8-23years, mean=16.2+/-3.3) underwent diagnostic (ADOS/ADI-R), as well as brain imaging assessments including RS fMRI (Bölte et al., 2014). Further behavioral investigations included IQ testing (WISC/WAIS) and autistic traits were assessed using the Social Responsiveness Scale (SRS). Functional images were pre-processed in AFNI, including nuisance signal regression (local white matter lateral ventricle signal) and motion-censoring. RS connectivity (temporal correlations) between major hubs of the DMN (posterior cingulate cortex: [-6,-44,34]; ventromedial prefrontal cortex: [-2,38,-12]) and the SN (right anterior insula:[39,23,-4]; anterior cingulate cortex: [6,24,32]), respectively, were calculated. Conditional linear regressions in R were used to model within-pair associations between RS connectivity and autistic traits while controlling for head motion and IQ. In a second step, analyses were repeated while stratifying by age (children: 8-13, N=44; adolescents: 14-17, N=62; adults: 18-23 years, N=44).

Results: A significant positive within-pair association was found in the whole sample between autistic traits and within-SN connectivity (i.e. between anterior insula and anterior cingulate cortex; β=0.003; Z=2.77; p=0.006; SEM=0.001). In contrast, a negative within-pair association between within-DMN connectivity (posterior cingulate to ventromedial prefrontal cortex) and autistic traits was found only after stratifying by age in adolescents (β=-0.002; Z=-2.24; p=0.025; SEM=0.001) and adults (β=-0.002; Z=-2.06; p=0.040; SEM=0.001) but not in children (β=0.00015; Z=1.426; p=0.154; SEM=0.001).

Conclusions: The results are in line with previous reports of altered RS connectivity in ASC and suggest SN and DMN connectivity as promising candidate biomarkers for ASC. They are further consistent with contemporary developmental models of ASC (Uddin, Supekar, and Menon, 2013), supporting the idea of early over-connectivity and under-connectivity later in life and underline the importance of testing for age effects. However, our results suggest that connectivity differences as well as developmental trajectories of the latter might be network-specific rather than generalizable across the brain.