Evidence map›Paper›PMID 42668271›Full record

SynthesisMolecular psychiatry2026

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

Cecilia Cabasino, Paolo Enrico, Federico Bottaro, Dalia De Santis, Cinzia Cagnoli, Rita Garbelli, Italia Bongarzone, Yvan Torrente, Giuseppe Delvecchio, Paolo Brambilla

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Molecular psychiatry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Cecilia Cabasino *Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, 20122, Milan, Italy.ORCID http://orcid.org/0009-0005-7124-3784
Paolo Enrico *Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, 20122, Milan, Italy.
Federico BottaroDepartment of Pathophysiology and Transplantation, University of Milan, 20122, Milan, Italy.
Dalia De SantisEpilepsy Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133, Milan, Italy.
Cinzia CagnoliEpilepsy Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133, Milan, Italy.ORCID http://orcid.org/0000-0001-6863-6687
Rita GarbelliEpilepsy Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133, Milan, Italy.
Italia BongarzoneDepartment of Diagnostic Innovation, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133, Milan, Italy.ORCID http://orcid.org/0000-0003-2530-9170
Yvan TorrenteNeurology Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, 20122, Milan, Italy.
Giuseppe DelvecchioDepartment of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, 20122, Milan, Italy.ORCID http://orcid.org/0000-0003-4750-1980
Paolo BrambillaDepartment of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, 20122, Milan, Italy. paolo.brambilla1@unimi.it.ORCID http://orcid.org/0000-0002-4021-8456

Funding

Ministero dell'Istruzione, dell'Università e della Ricerca (Ministry of Education, University and Research) 'Dipartimenti di Eccellenza' Programme 2023-27Ministero della Salute (Ministry of Health, Italy) HLS-DA, PNC-E3-2022-23683266- CUP: C43C22001630001 / MI-0117Ministero della Salute (Ministry of Health, Italy) RF-2019-12371066Ministero della Salute (Ministry of Health, Italy) Ricerca corrente 2025
6 · The paper itself

Abstract

backgroundLipids 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.

methodsA 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.

resultsFollowing 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.

conclusionsStudying 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.

Identifiers

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.