Neurogenetic analysis of childhood disintegrative disorder

Abstract

Background: Childhood disintegrative disorder (CDD) is a rare form of autism spectrum disorder (ASD) of unknown etiology. It is characterized by late-onset regression leading to significant intellectual disability (ID) and severe autism. Although there are phenotypic differences between CDD and other forms of ASD, it is unclear if there are neurobiological differences.

Methods: We pursued a multidisciplinary study of CDD (n = 17) and three comparison groups: low-functioning ASD (n = 12), high-functioning ASD (n = 50), and typically developing (n = 26) individuals. We performed whole-exome sequencing (WES), copy number variant (CNV), and gene expression analyses of CDD and, on subsets of each cohort, non-sedated functional magnetic resonance imaging (fMRI) while viewing socioemotional (faces) and non-socioemotional (houses) stimuli and eye tracking while viewing emotional faces.

Results: We observed potential differences between CDD and other forms of ASD. WES and CNV analyses identified one or more rare de novo, homozygous, and/or hemizygous (mother-to-son transmission on chrX) variants for most probands that were not shared by unaffected sibling controls. There were no clearly deleterious variants or highly recurrent candidate genes. Candidate genes that were found to be most conserved at variant position and most intolerant of variation, such as TRRAP, ZNF236, and KIAA2018, play a role or may be involved in transcription. Using the human BrainSpan transcriptome dataset, CDD candidate genes were found to be more highly expressed in non-neocortical regions than neocortical regions. This expression profile was similar to that of an independent cohort of ASD probands with regression. The non-neocortical regions overlapped with those identified by fMRI as abnormally hyperactive in response to viewing faces, such as the thalamus, cerebellum, caudate, and hippocampus. Eye-tracking analysis showed that, among individuals with ASD, subjects with CDD focused on eyes the most when shown pictures of faces.

Conclusions: Given that cohort sizes were limited by the rarity of CDD, and the challenges of conducting non-sedated fMRI and eye tracking in subjects with ASD and significant ID, this is an exploratory study designed to investigate the neurobiological features of CDD. In addition to reporting the first multimodal analysis of CDD, a combination of fMRI and eye-tracking analyses are being presented for the first time for low-functioning individuals with ASD. Our results suggest differences between CDD and other forms of ASD on the neurobiological as well as clinical level.

Keywords: Autism spectrum disorder (ASD); Childhood disintegrative disorder (CDD); Eye tracking; Functional magnetic resonance imaging (fMRI); Genetics; Intellectual disability (ID); Regression.

Fig. 1

Median expression levels of CDD candidate genes (n = 40) by brain region and time period (Additional file 2: Table S5) using the human BrainSpan exon-array transcriptome dataset [20]. The dark vertical line indicates birth. Log₂-transformed signal intensity ≥ 6 in at least one sample is considered positive expression [20]. AMY amygdala, CBC cerebellar cortex, HIP hippocampus MD mediodorsal nucleus of the thalamus, NCX neocortex, STR striatum

Fig. 2

Differential expression levels of various gene sets. The difference in median expression levels (non-neocortical minus neocortical brain regions) is shown for genes affected by non-synonymous or synonymous variants in CDD probands, their unaffected siblings, SSC probands with regression, and SSC probands without regression. The number in parentheses indicates the number of subjects or variants, and the dark vertical line in each panel indicates birth. For potential CDD candidate genes, the difference reaches a maximum positive value at period six (mid-fetal stages); significance was confirmed by permutation testing with 100,000 iterations of 40 randomly selected genes (P = 0.0022). CDD childhood disintegrative disorder, SSC Simons Simplex Collection

Fig. 3

Gene coexpression network analysis. Eleven of the 40 CDD candidate genes are coexpressed with at least one other candidate gene across all brain regions and time periods with a Pearson correlation coefficient r ≥ 0.7 (Additional file 2: Table S7), a mean of 2.09 correlations/gene (P = 0.036), and a mean coefficient of 0.779 (P = 0.019, permutation testing with 100,000 iterations of 40 randomly selected genes). Positive correlations are shown in blue, and negative correlations are shown in red. The greater the magnitude of the coefficient, the wider and darker are the edges. The size of a node is proportional to the number of edges the node has

Fig. 4

Brain regions of interest (ROIs) involved in processing socioemotional (fearful face) versus non-socioemotional (house) visual stimuli. a The green color brain map indicates regions of significant faces > houses activation in a discovery sample of 12 TD subjects (Z > 3.09, whole-brain corrected at the cluster-level P < 0.05). b These independently defined ROIs were then utilized for comparisons across the four remaining cohorts, a TD:validation sample (n = 7), HFASD (n = 14), LFASD (n = 7), and CDD (n = 7). The bar graph indicates the mean % signal change (faces > houses) for each cohort. Group differences were not significant when comparing the TD:validation and HFASD groups [t(19) = 0.17, P = 0.87, Cohen’s d = 0.08] and when comparing the LFASD and CDD groups [t(12) = 0.97, P = 0.35, Cohen’s d = 0.56]. The faces > houses response within the CDD group was not significantly greater than zero [t(6) = 0.80, P = 0.45, Cohen’s d = 0.30]. Error bars indicate standard error of the mean. All P values were calculated by independent t test and are two-tailed. FFG fusiform gyrus, L left, LOC lateral occipital cortex, MTG middle temporal gyrus, R right

Fig. 5

CDD whole-brain fMRI analysis. a The red color brain map indicates regions of significant faces > houses activation in the CDD subjects (Z > 3.09, whole-brain corrected at the cluster-level P < 0.05). b The bar graph indicates the mean % signal change (faces > houses) within these areas for each cohort: TD:discovery (n = 12), TD:validation (n = 7), HFASD (n = 14), LFASD (n = 7), and CDD (n = 7). The CDD cohort differed significantly from HFASD [t(19) = 2.98, P = 0.0076, Cohen’s d = 1.45] but not from LFASD [t(12) = 1.71, P = 0.11, Cohen’s d = 0.99]. Error bars indicate standard error of the mean. All P values were calculated by independent t test and are two-tailed. MFG middle frontal gyrus, PG precentral gyrus

Fig. 6

Behavioral analysis through eye tracking. The yellow and green bars of the graph represent the mean % of time spent fixating (y axis) on the eyes and mouth of the faces, respectively, by cohort (x axis): TD (n = 14), HFASD (n = 32), LFASD (n = 7), CDD (n = 5). The gaze heat maps illustrate the group-level gaze data overlaid on one of the images at which subjects looked. Compared to TD subjects, HFASD subjects show decreased fixation on the eyes [t(44) = -2.28, P = 0.03, Cohen’s d = 0.77] and increased fixation on the mouth [t(44) = 2.16, P = 0.04, Cohen’s d = 0.76]. The % of time subjects with LFASD spent looking at the eyes did not differ from HFASD [t(37) = 0.43, P = 0.67, Cohen’s d = 0.17], but CDD subjects fixated eyes significantly more than HFASD [t(35) = 2.19, P = 0.04, Cohen’s d = 1.08]. Error bars indicate standard error of the mean. All P values were calculated by independent t test and are two-tailed