Although neuritic plaques - comprised of aggregated fibrils of the misfolded protein, amyloid β (Aβ) - have formed a central focus of Alzheimer's disease (AD) research for decades, it is now well understood that plaque burden alone is a poor correlate of cognitive decline. This is highlighted especially when compared against other neuropathological hallmarks, such as synapse loss (the strongest correlate) and hyperphosphorylated protein tau. However, it is known that Familial AD arises due to autosomal dominant mutations directly influencing the generation of Aβ, suggesting that Aβ pathology may play a key upstream role in the disease. Such contrasting lines of evidence have thus raised questions as to why some aged individuals with high plaque burden develop AD while others remain cognitively healthy. In their recent study, published in Analytical Chemistry (June 2024), Enzlein and colleagues aimed to investigate whether differences in the molecular composition of plaques between individuals with sporadic Alzheimer's disease (N = 9) versus age-matched amyloid positive but cognitively unaffected controls (N = 8) could go towards explaining this outstanding question in the field. Using novel methods integrating mass spectrometry imaging with machine learning feature extraction, the authors compared peptide and lipid profiles to a resolving limit of 400 μm2 for >5000 individual plaques. In doing so, a distinct peptide signature was identified in sporadic Alzheimer's disease plaques that was characterised by strongly increased aggregation of the short amyloid β isoform, Aβ1-38 coupled with a lesser co-aggregation of pyroglutamate-modified Aβ3-42pE. Sporadic Alzheimer's disease plaques also demonstrated a robust lipid signature denoted by an increased presence of cell membrane components, GM1 and GM2 gangliosides. Here, we review this work; aiming to place these findings within the context of existing literature and with a view to discussing their importance in developing our current knowledge of Alzheimer's disease.
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