Spatial lipidomics of the human brain: systematic review of current state and future perspectives

Lipids represent a significant component of the human brain, exerting crucial functions in both physiological and pathological conditions. Mapping brain lipids distribution is an emerging area of research, with mass spectrometry imaging allowing the detection of lipid species and their localization within tissue sections. However, comprehensive spatial mapping of lipids in the human brain remains to be achieved. This systematic review addresses this gap by critically synthesizing the available literature in the field.

A bibliographic search on PubMed, Scopus and Web of Science for original articles employing mass spectrometry imaging to analyze lipids and their distribution in the human brain was performed. The included articles were grouped according to the clinical characteristics of the studied populations, including healthy subjects and selected neurological and psychiatric disorders. Studies on human brain tissue from tumoral specimens, animals, or in vitro models such as organoids were excluded to maintain focus on translational findings directly applicable to human neurological and psychiatric diseases.

Following the inclusion criteria, 34 articles were selected. Alzheimer's disease, schizophrenia and multiple sclerosis were the most frequently investigated conditions, alongside studies in healthy subjects describing lipid distribution under physiological conditions. We observed considerable heterogeneity across studies in terms of research questions and methodological approaches. Nevertheless, our critical synthesis allowed us to identify both consistencies and discrepancies in experimental strategies and in the lipid signatures reported.

Studying lipids by mass spectrometry imaging enables the identification of spatially defined profiles in distinct brain areas, providing valuable insights into both human neurobiology and brain disorders' pathophysiology. In this context, spatial information is crucial for linking lipid alterations to specific structures or lesions, thereby supporting translational applications. Finally, we identified key methodological issues that must be addressed to advance this emerging field.