Distinct Virtual Histology of Grey Matter Atrophy in Four Neuroinflammatory Diseases

Rheumatology and Immunology Neurology Biophysics Medical Imaging Life Sciences Immunology Medicine
virtual histology grey matter atrophy multiple sclerosis NMOSD MOGAD

Research Background

The core focus of this study is the manifestation of gray matter atrophy in neuroinflammatory diseases. Gray matter atrophy typically appears in four types of neuroinflammatory demyelinating diseases: Multiple Sclerosis (MS), Neuromyelitis Optica Spectrum Disorders (NMOSD) positive (AQP4+) and negative (AQP4-) for aquaporin-4 antibody, and Myelin Oligodendrocyte Glycoprotein Antibody-Associated Disease (MOGAD). Understanding the pathobiological basis of gray matter atrophy in these diseases aids in their differential diagnosis and guides treatment strategies. However, there is currently a lack of systematic research on the mechanisms of gray matter atrophy.

Paper Source

This paper was jointly written by scholars Jun Sun, Min Guo, Li Chai, Siyao Xu, and Yuerong Lizhu, affiliated with Beijing Tiantan Hospital, Capital Medical University, Huashan Hospital, Fudan University, among others, and was published in 2024 in the journal “Brain.”

Research Process

Data Source and Sample

This study analyzed data from a multicenter cohort of 2812 participants, including 324 MS patients, 197 AQP4+ NMOSD patients, 75 AQP4- NMOSD patients, 47 MOGAD patients, and 2169 healthy controls (HCs).

Data Processing and Analysis

  1. Gray Matter Atrophy Assessment: Three-dimensional T1-weighted images were used, and gray matter volume was obtained using the FreeSurfer software (command: recon-all). Cohen’s d values were calculated to assess the characteristics of gray matter atrophy for each disorder, analyzing changes in gray matter volume among different disease groups.

  2. Virtual Histology Analysis: Gene expression data from the Allen Human Brain Atlas (AHBA) were mapped onto 41 brain regions, and genes suitable for analysis were further selected using single-cell RNA sequencing data. The spatial correlation between the expression levels of each selected cell type’s genes and gray matter atrophy characteristics was calculated.

Clinical Feature Correlation Analysis

Based on patients’ clinical features (such as physical disability, disease duration, number of relapses, lesion volume, cognitive function, etc.), subgroup analysis was conducted to explore the association between these features and gray matter atrophy.

Data Analysis Methods

ANOVA and subsequent t-tests were used to analyze the relationship between gray matter atrophy and various clinical features. Principal Component Analysis (PCA) and Hierarchical Clustering Analysis were applied to explore the similarities and differences in gray matter atrophy characteristics among the four types of neuroinflammatory diseases.

Research Results

General Characteristics of Gray Matter Atrophy

  1. Multiple Sclerosis: Gray matter atrophy was mainly concentrated in the subcortical nuclei and brainstem.

  2. AQP4+ NMOSD: Significant widespread gray matter atrophy was primarily located in the occipital cortex and cerebellum.

  3. AQP4- NMOSD: Mild gray matter atrophy was mainly concentrated in the frontal and parietal cortices.

  4. MOGAD: Gray matter atrophy was concentrated in the frontal and temporal cortices.

Virtual Histology Analysis

  1. Multiple Sclerosis: Gene expression associated with microglia, astrocytes, oligodendrocytes, and endothelial cells was significantly correlated with gray matter atrophy characteristics.

  2. AQP4+ NMOSD: Gene expression associated with S1 pyramidal cells was significantly correlated with gray matter atrophy characteristics.

  3. MOGAD: Gene expression associated with CA1 and S1 pyramidal cells was significantly correlated with gray matter atrophy characteristics.

  4. AQP4- NMOSD: No specific central nervous system cell types were found to be significantly correlated with gray matter atrophy characteristics.

PCA and Hierarchical Clustering Analysis

The PCA results showed that the first and second principal components explained 47.4% and 26.2% of the variance in gray matter atrophy characteristics, respectively, indicating significant heterogeneity between disease groups. Hierarchical clustering analysis subdivided the four types of neuroinflammatory diseases into different subtypes, but the virtual histology results were consistent across all subtypes.

Clinical Feature Correlation Analysis

  1. Multiple Sclerosis: Patients with higher EDSS scores showed more significant gray matter atrophy in the subcortical nuclei, reflecting the characteristics of neural cell damage during the progressive phase.

  2. AQP4- NMOSD: Patients with more relapses showed significant gray matter atrophy in the parietal cortex, suggesting that disease progression may be related to insufficient neural protection.

  3. MOGAD: Patients with lower MoCA scores showed more gray matter atrophy in the frontal and temporal cortices, highlighting the importance of neural and endothelial cell damage in cognitive decline.

Research Conclusion

This study comprehensively revealed the characteristics and pathological basis of gray matter atrophy in MS, AQP4+ NMOSD, AQP4- NMOSD, and MOGAD patients through virtual histology methods. The main target cells in MS are microglia, astrocytes, and oligodendrocytes; AQP4+ NMOSD primarily involves astrocytes; MOGAD’s gray matter atrophy is mainly due to oligodendrocyte dysfunction. Additionally, neural and endothelial cells are potential common targets in these neuroinflammatory diseases. These findings provide important evidence for the differential diagnosis and optimized treatment of neuroinflammatory diseases.