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A molecular map of the living human brain from quantitative MRI

Grant-Peters, M.; Thomas, G. E. C.; Kruining, D. v.; Huuki-Myers, L. A.; Zhang, R.; Brenton, J. W.; Nelvagal, H.; Zarkali, A.; Evans, J. R.; Toomey, C. E.; Fairbrother-Browne, A.; Dobreva, I.; Montgomery, K. D.; Lachica, J.; Hannaway, N.; Wood, N.; Gandhi, S.; Callaghan, M. F.; Platt, F. M.; Jaunmuktane, Z.; Shmueli, K.; Collado Torres, L.; Maynard, K.; Weil, R.; Ryten, M.

2026-01-29 neuroscience
10.1101/2025.09.24.678316 bioRxiv
Show abstract

Profiling dynamic molecular processes in neurodegeneration in vivo remains a major clinical challenge. Limited brain tissue accessibility especially limits the development and effective deployment of emerging disease modifying therapies, highlighting the need for non-invasive methods for profiling molecular disease processes. We introduce a non-invasive imaging framework that integrates ultra-high-resolution 7T quantitative MRI (qMRI) with spatially-resolved transcriptomics (SRT) to infer cell-type and pathway-specific molecular features within the cortical grey matter. This proof-of-concept establishes the integration of qMRI and SRT as a scalable, non-invasive platform for molecular profiling in neurodegeneration, with significant potential for precision therapeutic monitoring, drug development and clinical trials.

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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.