Quantitative neuropathology: an update on automated methodologies and implications for large scale cohorts

Area of Science:

• Neuroscience
• Neuropathology
• Biomedical Engineering

Background:

• Tissue microarrays (TMAs) are established tools for neurodegenerative disease research.
• Previous studies highlight the need to understand pathology load variations in neurodegenerative diseases.

Purpose of the Study:

• To investigate pathology load variations across semi-quantitative score categories in neurodegenerative diseases.
• To determine the relationship between pathology load and disease progression.
• To leverage quantitative data from TMAs for improved clinical stratification.

Main Methods:

• Utilized post-mortem brain tissue from 146 cases (Alzheimer's disease, Lewy body disease, mixed, and controls).
• Constructed TMAs from 15 brain regions per case.
• Stained for hyperphosphorylated tau (HP-T), beta-amyloid, and alpha-synuclein (αsyn), quantifying loads via automated image analysis.

Main Results:

• Demonstrated wide variations in HP-T, β-amyloid, and αsyn pathology loads, even within severe disease classifications (e.g., Braak stage VI, Thal phase 5, McKeith neocortical LBD).
• HP-T load predicted Braak stage in AD/control cases (p < 0.001).
• β-amyloid load predicted Thal phase (p < 0.001), and αsyn load predicted LBD type (p < 0.001).

Conclusions:

• Quantitative TMA data reveal substantial heterogeneity in pathological loads across neurodegenerative disease cases.
• This detailed pathological quantification aids in understanding disease complexity and identifying novel clinico-pathological phenotypes.
• Improved stratification of clinical cohorts based on underlying pathologies can enhance research and treatment strategies.