| Examining the validity of the use of ratio IQs in psychological assessments | 10.15154/1522624 | IQ tests are amongst the most used psychological assessments, both in research and clinical settings. For participants who cannot complete IQ tests normed for their age, ratio IQ scores (RIQ) are routinely computed and used as a proxy of IQ, especially in large research databases to avoid missing data points. However, because it has never been scientifically validated, this practice is questionable. In the era of big data, it is important to examine the validity of this widely used practice. In this paper, we use the case of autism to examine the differences between standard full-scale IQ (FSIQ) and RIQ. Data was extracted from four databases in which ages, FSIQ scores and subtests raw scores were available for autistic participants between 2 and 17 years old. The IQ tests included were the MSEL (N=12033), DAS-II early years (N=1270), DAS-II school age (N=2848), WISC-IV (N=471) and WISC-V (N=129). RIQs were computed for each participant as well as the discrepancy (DSC) between RIQ and FSIQ. We performed two linear regressions to respectively assess the effect of FSIQ and of age on the DSC for each IQ test, followed by additional analyses comparing age subgroups as well as FSIQ subgroups on DSC. Participants at the extremes of the FSIQ distribution tended to have a greater DSC than participants with average FSIQ. Furthermore, age significantly predicted the DSC, with RIQ superior to FSIQ for younger participants while the opposite was found for older participants. These results question the validity of this widely used alternative scoring method, especially for individuals at the extremes of the normal distribution, with whom RIQs are most often employed. | 137/17423 | Secondary Analysis | Shared |
| The striatal matrix compartment is expanded in autism spectrum disorder. | 10.15154/khn8-jf08 | Background: Autism spectrum disorder (ASD) is the second-most common neurodevelopmental disorder in childhood. This complex developmental disorder that manifests with restricted interests, repetitive behaviors, and difficulties in communication and social awareness. The inherited and acquired causes of ASD impact many and diverse brain regions, challenging efforts to identify a shared neuroanatomical substrate for this range of symptoms. The striatum and its connections are among the most implicated sites of abnormal structure and/or function in ASD. Striatal projection neurons develop in segregated tissue compartments, the matrix and striosome, that are histochemically, pharmacologically, and functionally distinct. Immunohistochemical assessment of ASD and animal models of autism described abnormal matrix:striosome volume ratios, with an possible shift from striosome to matrix volume. Shifting the matrix:striosome ratio could result from expansion in matrix, reduction in striosome, spatial redistribution of the compartments, or a combination of these changes. Each type of ratio-shifting abnormality may predispose to ASD but yield different combinations of ASD features.
Methods: We developed a cohort of 426 children and adults (213 matched ASD-control pairs) and
performed connectivity-based parcellation (diffusion tractography) of the striatum. This identified voxels with matrix-like and striosome-like patterns of structural connectivity.
Results: Matrix-like volume was increased in ASD, with no evident change in the volume or organization of the striosome-like compartment. The inter-compartment volume difference (matrix minus striosome) within each individual was 31% larger in ASD. Matrix-like volume was increased in both caudate and putamen, and in somatotopic zones throughout the rostral-caudal extent of the striatum. Subjects with moderate elevations in ADOS (Autism Diagnostic Observation Schedule) scores had increased matrix-like volume, but those with highly elevated ADOS scores had 3.7-fold larger increases in matrix-like volume.
Conclusions: Matrix and striosome are embedded in distinct structural and functional networks, suggesting that compartment-selective injury or maldevelopment may mediate specific and distinct clinical features. Previously, assessing the striatal compartments in humans required post mortem tissue. Striatal parcellation provides a means to assess neuropsychiatric diseases for compartment-specific abnormalities in vivo. While this ASD cohort had increased matrix-like volume, other mechanisms that shift the matrix:striosome ratio may also increase the chance of developing the diverse social, sensory, and motor phenotypes of ASD.
| 1/2166 | Secondary Analysis | Shared |
| Imbalanced social-communicative and restricted repetitive behavior subtypes in autism spectrum disorder exhibit different neural circuitry | 10.15154/1524418 | Social-communication (SC) and restricted repetitive behaviors (RRB) are autism diagnostic symptom domains. SC and RRB severity can markedly differ within and between individuals and may be underpinned by different neural circuitry and genetic mechanisms. Modeling SC-RRB balance could help identify how neural circuitry and genetic mechanisms map onto such phenotypic heterogeneity. Here, we developed a phenotypic stratification model that makes highly accurate (97–99%) out-of-sample SC = RRB, SC > RRB, and RRB > SC subtype predictions. Applying this model to resting state fMRI data from the EU-AIMS LEAP dataset (n = 509), we find that while the phenotypic subtypes share many commonalities in terms of intrinsic functional connectivity, they also show replicable differences within some networks compared to a typically-developing group (TD). Specifically, the somatomotor network is hypoconnected with perisylvian circuitry in SC > RRB and visual association circuitry in SC = RRB. The SC = RRB subtype show hyperconnectivity between medial motor and anterior salience circuitry. Genes that are highly expressed within these networks show a differential enrichment pattern with known autism-associated genes, indicating that such circuits are affected by differing autism-associated genomic mechanisms. These results suggest that SC-RRB imbalance subtypes share many commonalities, but also express subtle differences in functional neural circuitry and the genomic underpinnings behind such circuitry. | 100/1708 | Secondary Analysis | Shared |
| comparing EEG metrics during eyes closed versus eyes open rest in autism | 10.15154/1528590 | Understanding the complex relationship between brain dynamics and mental disorders has proved difficult. Sample sizes have often been small, and brain dynamics have often been evaluated in only one state. Here, data obtained from the NIMH data archive were used to create a sample of 395 individuals with both eyes open and eyes closed resting state EEG data. All data were submitted to a standard pipeline to extract power spectra, peak alpha frequency, the slope of the 1/f curve, multi scale sample entropy, phase amplitude coupling, and intersite phase clustering. These data along with the survey data collected at the time of data collection form a valuable resource for interogating the relationship between brain state changes and autism diagnosis. | 3/336 | Secondary Analysis | Shared |
| Structural brain alterations in autism: A voxel-based morphometry mega-analysis in 3,051 participants across 51 sites | 10.15154/t4ey-q854 | Background: Previous large-scale structural MRI analyses of the brain in autism have identified gray matter (GM) differences when using region-of-interest analyses based on gross anatomical regions. However, such analyses have limited spatial specificity and may obscure subtle focal differences. Whole brain voxel-based morphometry (VBM) analyses enable greater spatial precision to identify and localize previously undetected neuroanatomical alterations.
Purpose: To rigorously identify voxel-wise GM and white matter (WM) volume differences in autism in the largest VBM mega-analysis to date.
Materials and Methods: This retrospective mega-analysis included structural 3D volumetric T1-weighted MRI brain scans from 3,051 participants (15.0 ± 8.2 yrs; 76.8% male; 1,519 autism; 1,532 neurotypicals) collected across 51 sites/scanners. Voxel-wise GM and WM volumes were quantified using the ENIGMA CAT12 VBM pipeline. Linear mixed-effects regression was performed at each voxel to evaluate the association between diagnostic group and voxel-wise volume while adjusting for standard nuisance covariates
Results: Autism was associated with widespread lower GM volume involving cortical, subcortical, and cerebellar regions (peak t=7.39, peak β=0.13); such GM differences were most notably detected in the bilateral orbitofrontal cortex, amygdala, thalamus, and posterior lobes of the cerebellum. WM volume was lower in autism across major projection, commissural, association, and cerebellar/brainstem tracts (peak t=6.74, peak β=0.08), including the corona radiata, internal capsule, corpus callosum, and cerebellar peduncles. These findings remained consistent in sensitivity analyses, including covarying for full-scale IQ and the application of increasingly strict motion exclusion criteria.
Conclusion: Autism is associated with smaller voxel-wise GM and WM volume involving widespread cortical, subcortical, and cerebellar regions. This high-resolution identification and localization of structural brain differences support the involvement of distributed neural systems in autism that underlie reward processing, sensory integration, and motor functioning in autism. | 3/311 | Secondary Analysis | Shared |