Cortical Thickness Differences Are Associated With Chemical Synaptic Transmission Upregulated Genes in Degeneration of Mild Cognitive Impairment

Morphometric similarity differences in drug-naive Parkinson's disease correlate with transcriptomic signatures

BACKGROUND

Differences in cortical morphology have been reported in individuals with Parkinson's disease (PD). However, the pathophysiological mechanism of transcriptomic vulnerability in local brain regions remains unclear.

OBJECTIVE

This study aimed to characterize the morphometric changes of brain regions in early drug-naive PD patients and uncover the brain-wide gene expression correlates.

METHODS

The morphometric similarity (MS) network analysis was used to quantify the interregional structural similarity from multiple magnetic resonance imaging anatomical indices measured in each brain region of 170 early drug-naive PD patients and 123 controls. Then, we applied partial least squares regression to determine the relationship between regional changes in MS and spatial transcriptional signatures from the Allen Human Brain Atlas dataset, and identified the specific genes related to MS differences in PD. We further investigated the biological processes by which the PD-related genes were enriched and the cellular characterization of these genes.

RESULTS

Our results showed that MS was mainly decreased in cingulate, frontal, and temporal cortical areas and increased in parietal and occipital cortical areas in early drug-naive PD patients. In addition, genes whose expression patterns were associated with regional MS changes in PD were involved in astrocytes, excitatory, and inhibitory neurons and were functionally enriched in neuron-specific biological processes related to trans-synaptic signaling and nervous system development.

CONCLUSIONS

These findings advance our understanding of the microscale genetic and cellular mechanisms driving macroscale morphological abnormalities in early drug-naive PD patients and provide potential targets for future therapeutic trials.

Pangenomics: A new era in the field of neurodegenerative diseases

A pangenome is composed of all the genetic variability of a group of individuals, and its application to the study of neurodegenerative diseases may provide valuable insights into the underlying aspects of genetic heterogenetiy for these complex ailments, including gene expression, epigenetics, and translation mechanisms. Furthermore, a reference pangenome allows for the identification of previously undetected structural commonalities and differences among individuals, which may help in the diagnosis of a disease, support the prediction of what will happen over time (prognosis) and aid in developing novel treatments in the perspective of personalized medicine. Therefore, in the present review, the application of the pangenome concept to the study of neurodegenerative diseases will be discussed and analyzed for its potential to enable an improvement in diagnosis and prognosis for these illnesses, leading to the development of tailored treatments for individual patients from the knowledge of the genomic composition of a whole population.

Case-control virtual histology elucidates cell types associated with cortical thickness differences in Alzheimer's disease

Many neuropsychiatric disorders are characterised by altered cortical thickness, but the cell types underlying these changes remain largely unknown. Virtual histology (VH) approaches map regional patterns of gene expression with regional patterns of MRI-derived phenotypes, such as cortical thickness, to identify cell types associated with case-control differences in those MRI measures. However, this method does not incorporate valuable information of case-control differences in cell type abundance. We developed a novel method, termed case-control virtual histology (CCVH), and applied it to Alzheimer's disease (AD) and dementia cohorts. Leveraging a multi-region gene expression dataset of AD cases (n = 40) and controls (n = 20), we quantified AD case-control differential expression of cell type-specific markers across 13 brain regions. We then correlated these expression effects with MRI-derived AD case-control cortical thickness differences across the same regions. Cell types with spatially concordant AD-related effects were identified through resampling marker correlation coefficients. Among regions thinner in AD, gene expression patterns identified by CCVH suggested fewer excitatory and inhibitory neurons, and greater proportions of astrocytes, microglia, oligodendrocytes, oligodendrocyte precursor cells, and endothelial cells in AD cases vs. controls. In contrast, original VH identified expression patterns suggesting that excitatory but not inhibitory neuron abundance was associated with thinner cortex in AD, despite the fact that both types of neurons are known to be lost in the disorder. Compared to original VH, cell types identified through CCVH are more likely to directly underlie cortical thickness differences in AD. Sensitivity analyses suggest our results are largely robust to specific analysis choices, like numbers of cell type-specific marker genes used and background gene sets used to construct null models. As more multi-region brain expression datasets become available, CCVH will be useful for identifying the cellular correlates of cortical thickness across neuropsychiatric illnesses.

Cortical thickness differences are associated with cellular component morphogenesis of astrocytes and excitatory neurons in nonsuicidal self-injuring youth

Nonsuicidal self-injury (NSSI) generally occurs in youth and probably progresses to suicide. An examination of cortical thickness differences (ΔCT) between NSSI individuals and controls is crucial to investigate potential neurobiological correlates. Notably, ΔCT are influenced by specific genetic factors, and a large proportion of cortical thinning is associated with the expression of genes that overlap in astrocytes and pyramidal cells. However, in NSSI youth, the mechanisms underlying the relations between the genetic and cell type-specific transcriptional signatures to ΔCT are unclear. Here, we studied the genetic association of ΔCT in NSSI youth by performing a partial least-squares regression (PLSR) analysis of gene expression data and 3D-T1 brain images of 45 NSSI youth and 75 controls. We extracted the top-10 Gene Ontology terms for the enrichment results of upregulated PLS component 1 genes related to ΔCT to conduct the cell-type classification and enrichment analysis. Enrichment of cell type-specific genes shows that cellular component morphogenesis of astrocytes and excitatory neurons accounts for the observed NSSI-specific ΔCT. We validated the main results in independent datasets to verify the robustness and specificity. We concluded that the brain ΔCT is associated with cellular component morphogenesis of astrocytes and excitatory neurons in NSSI youth.