Morphometric network-based abnormalities correlate with psychiatric comorbidities and gene expression in PCDH19-related developmental and epileptic encephalopathy

Abstract

Protocadherin-19 (PCDH19) developmental and epileptic encephalopathy causes an early-onset epilepsy syndrome with limbic seizures, typically occurring in clusters and variably associated with intellectual disability and a range of psychiatric disorders including hyperactive, obsessive-compulsive and autistic features. Previous quantitative neuroimaging studies revealed abnormal cortical areas in the limbic formation (parahippocampal and fusiform gyri) and underlying white-matter fibers. In this study, we adopted morphometric, network-based and multivariate statistical methods to examine the cortex and substructure of the hippocampus and amygdala in a cohort of 20 PCDH19-mutated patients and evaluated the relation between structural patterns and clinical variables at individual level. We also correlated morphometric alterations with known patterns of PCDH19 expression levels. We found patients to exhibit high-significant reductions of cortical surface area at a whole-brain level (left/right p_value = 0.045/0.084), and particularly in the regions of the limbic network (left/right parahippocampal gyri p_value = 0.230/0.016; left/right entorhinal gyri p_value = 0.002/0.327), and bilateral atrophy of several subunits of the amygdala and hippocampus, particularly in the CA regions (head of the left CA3 p_value = 0.002; body of the right CA3 p_value = 0.004), and differences in the shape of hippocampal structures. More severe psychiatric comorbidities correlated with more significant altered patterns, with the entorhinal gyrus (p_value = 0.013) and body of hippocampus (p_value = 0.048) being more severely affected. Morphometric alterations correlated significantly with the known expression patterns of PCDH19 (r_value = -0.26, p_spin = 0.092). PCDH19 encephalopathy represents a model of genetically determined neural network based neuropsychiatric disease in which quantitative MRI-based findings correlate with the severity of clinical manifestations and had have a potential predictive value if analyzed early.

Fig. 1. Correlation patterns in clinical variables.

Correlation patterns between age at seizure onset and cognitive level (A) and severity of psychiatric disorder (B) in the cohort of patients with PCDH19-gene-related syndrome. Cognitive level was classified as follow: (0) “normal” or (1) “mild ID” or (2) “moderate ID” or (3) “severe ID”. Clinical values are summarized in Table 1.

Fig. 2. Morphometric analysis.

Statistical ROI-based morphometric analysis of PCDH19-patients compared with matched controls. The results of the regression analysis on morphometric features, surface area (SA, A) and cortical thickness (CT, B), are represented by β₂ maps (specified in Supplementary Table 1) superimposed on the pial surfaces of the left and right hemispheres. We observed statistically significant lower values of SA in left and right temporo-limbic cortices (blue ROIs, A), and normal SA in the surrounding regions (green ROIs, panel A). CT was significantly increased in right lateral occipital gyrus and parahippocampal regions bilaterally (yellow ROIs, B).

Fig. 3. Network-based structural analysis of surface area (SA).

Spatial correlations (r_value, blue-red colormap) between SA patterns (β₂) and seed-based cortico-cortical (A) and subcortico-cortical (B) connectivity profiles. In this example, we used as seed the left entorhinal gyrus. Correlation scores (r_value) are detailed in Supplementary Tables 2 and 3. SA changes (β₂) are indicated in Supplementary Table 1.

Fig. 4. PCDH19-expression patterns and relationship with structural morphometric analysis.

Spatial PCDH19 expression patterns (ε_value) in cortical (A) and subcortical (B) regions of interest and (C) correlation between levels of PCDH19 expression and surface area changes (β₂ detailed in Supplementary Table 1) observed in cortical and subcortical regions. The statistical correlation highlighted that regions with higher level of PCDH19 expression exhibited significantly higher reductions in SA (r_value = -0.262, p_spin = 0.092).

Fig. 5. Grade of psychiatric comorbidities and relationship with structural morphometric analysis.

Significant regression patterns between the severity of psychiatric comorbidities and values of surface area (SA) of a representative subset of the cortical regions (left and right entorhinal, A and D; left and right fusiform, B and E; left and right inferiortemporal, C and F; left and right medialorbitofrontal, G and J; left and right rostralanteriorcingulate, H and K; left and right rostralmiddlefrontal, I and L, as reported in Supplementary Table 4) in PCDH19-mutated patients. The values, indicated by asterisks, are adjusted according to the linear regression model applied in the statistical analysis. The continuous line represents the fitting line, the dotted line indicated the 95% confidence bounds. We observed a negative trend in the fitting lines, that show a reduced SA in patients with more severe psychiatric disorder. Legend: lh, left hemisphere; rh, right hemisphere.