Spatial transcriptomics (ST) is revolutionizing our understanding of the central nervous system (CNS) by providing spatially resolved gene expression data. This mini review explores the impact of ST on CNS research, particularly in neurodegenerative diseases like Alzheimer’s, Parkinson’s, multiple sclerosis, and amyotrophic lateral sclerosis. We describe two foundational ST methods: sequencing-based and imaging-based. Key studies are reviewed highlighting the power of ST data sets to map transcriptomes to disease-specific histomorphology, elucidate molecular mechanisms of regional and cellular vulnerability, integrate single-cell data with tissue mapping, and reveal receptor-ligand interactions. Despite current challenges like data interpretation and resolution limits, ST holds promise for identifying novel drug targets, evaluating their therapeutic potential, and bridging gaps between animal models and human studies to advance development of CNS-targeting compounds.
BrummerTSchillnerMSteffenF, et al. Spatial transcriptomics and neurofilament light chain reveal changes in lesion patterns in murine autoimmune neuroinflammation. J. Neuroinflammation. 2023;20(1):1-17. doi:10.1186/s12974-023.
2.
ChenASunYLeiY, et al. Single-cell spatial transcriptome reveals cell-type organization in the macaque cortex. Cell. 2023;186(17):3726-3743e24. doi:10.1016/j.cell.2023.06.009.
3.
ChenSChangYLiL, et al. Spatially resolved transcriptomics reveals genes associated with the vulnerability of middle temporal gyrus in Alzheimer’s disease. Acta Neuropathol. Commun. 2022;10(1):1-24. doi:10.1186/s40478-022.
4.
ChenWTLuACraessaertsK, et al. Spatial transcriptomics and in situ sequencing to study Alzheimer’s disease. Cell. 2020;182(4):976,e-991.e19. doi:10.1016/j.cell.2020.06.038.
5.
DimitrovDSchäferPSLFarrE, et al. LIANA+ provides an all-in-one framework for cell–cell communication inference. Nat. Cell Biol. 2024;26(9):1613-1622. doi:10.1038/s41556-024-01469-w.
6.
GarmireLXLiYHuangQ, et al. Challenges and perspectives in computational deconvolution of genomics data. Nat. Methods. 2024;21(3):391-400. doi:10.1038/s41592-023-02166-6.
7.
GoodwinSMcPhersonJDMcCombieWR.Coming of age: ten years of next-generation sequencing technologies. Nat Rev Genet. 2016;17(6):333-351. doi:10.1038/nrg.2016.49.
8.
GoralskiTMMeyerdirkLBretonL, et al. Spatial transcriptomics reveals molecular dysfunction associated with cortical Lewy pathology. Nat. Commun. 2024;15(1):1-20. doi:10.1038/s41467-024-47027-8.
9.
GuoJYouLZhouY, et al. Spatial enrichment and genomic analyses reveal the link of NOMO1 with amyotrophic lateral sclerosis. Brain. 2024;147(8):2826-2841. doi:10.1093/brain/awae123.
10.
HahnKAmbergBMonné RodriguezJM, et al. Points to consider from the ESTP Pathology 2.0 Working Group: overview on spatial omics technologies supporting drug discovery and development. Toxicol Pathol. 2025;53(1):107-129. doi:10.1177/01926233241311258.
11.
HanBZhouSZhangY, et al. Integrating spatial and single-cell transcriptomics to characterize the molecular and cellular architecture of the ischemic mouse brain. Sci Transl Med. 2024;16(733):eadg1323. doi:10.1126/scitranslmed.adg1323.
12.
JungNKimTK.Spatial transcriptomics in neuroscience. Exp Mol Med. 2023;55(10):2105-2115. doi:10.1038/s12276-023-01093-y.
13.
KaufmannMEvansHSchauppAL, et al. Identifying CNS-colonizing T cells as potential therapeutic targets to prevent progression of multiple sclerosis. Med. 2021;2(3):296-312e8. doi:10.1016/j.medj.2021.01.006.
14.
KaufmannMSchauppALSunR, et al. Identification of early neurodegenerative pathways in progressive multiple sclerosis. Nat Neurosci. 2022;25(7):944-955. doi:10.1038/s41593-022-01097-3.
15.
KilfeatherPKhooJHWagnerK, et al. Single-cell spatial transcriptomic and translatomic profiling of dopaminergic neurons in health, aging, and disease. Cell Rep. 2024;43(3):113784. doi:10.1016/j.celrep.2024.113784.
16.
KwonSHParthibanSTippaniM, et al. Influence of Alzheimer’s disease related neuropathology on local microenvironment gene expression in the human inferior temporal cortex. GEN Biotechnology. 2023;2(5):399-417. doi:10.1089/genbio.2023.0019.
17.
LamMLeeDKosaterI, et al. Human disease-specific cell signatures in non-lesional tissue in Multiple Sclerosis detected by single-cell and spatial transcriptomics [published online ahead of print December 30, 2023]. Biorxiv. doi:10.1101/2023.12.20.572491.
18.
MallachAZielonkaMvan LieshoutV, et al. Microglia-astrocyte crosstalk in the amyloid plaque niche of an Alzheimer’s disease mouse model, as revealed by spatial transcriptomics. Cell Rep. 2024;43(6):114216. doi:10.1016/j.celrep.2024.114216.
19.
ManiatisSÄijöTVickovicS, et al. Spatiotemporal dynamics of molecular pathology in amyotrophic lateral sclerosis. Science. 2019;364(6435):89-93. doi:10.1126/science.aav9776.
20.
MaynardKRCollado-TorresLWeberLM, et al. Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex. Nat Neurosci. 2021;24(3):425-436. doi:10.1038/s41593-020-00787-0.
21.
MiyoshiEMorabitoSHenningfieldCM, et al. Spatial and single-nucleus transcriptomic analysis of genetic and sporadic forms of Alzheimer’s Disease. Biorxiv. 2023;56:5704-5717. doi:10.1101/2023.07.24.550282.
22.
MoffittJRBambah-MukkuDEichhornSW, et al. Molecular, spatial, and functional single-cell profiling of the hypothalamic preoptic region. Science. 2018;362(6416):eaau5324. doi:10.1126/science.aau5324.
23.
PiweckaMRajewskyNRybak-WolfA.Single-cell and spatial transcriptomics: deciphering brain complexity in health and disease. Nat Rev Neurol. 2023;19(6):346-362. doi:10.1038/s41582-023-00809-y.
24.
SmirnovAMelinoGCandiE.Gene expression in organoids: an expanding horizon. Biol. Direct. 2023;18(1):1-12. doi:10.1186/s13062-023-00360-2.
25.
SmithKDPrinceDKMacDonaldJWBammlerTKAkileshS.Challenges and opportunities for the clinical translation of spatial transcriptomics technologies. Glomerular Dis. 2024;4(1):49-63. doi:10.1159/000538344.
26.
StåhlPLSalménFVickovicS, et al. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science. 2016;353(6294):78-82. doi:10.1126/science.aaf2403.
27.
UzquianoAKedaigleAJPigoniM, et al. Proper acquisition of cell class identity in organoids allows definition of fate specification programs of the human cerebral cortex. Cell. 2022;185(20):3770.e-3788.e27. doi:10.1016/j.cell.2022.09.010.
28.
YaDZhangYCuiQ, et al. Application of spatial transcriptome technologies to neurological diseases. Front Cell Dev Biol. 2023;11:11. doi:10.3389/fcell.2023.1142923.
29.
YaoZvan VelthovenCTJKunstM, et al. A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain. Nature. 2023;624(7991):317-332. doi:10.1038/s41586-023-06812-z.
