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High-Dimensional Multi-Omic Mapping of Post-Mortem Human Brain Using Iterative Indirect Immunofluorescence Imaging on Xenium-Processed Tissues
Karaahmet B, Lama T, Wang A, Cao W, Menon V, Klein H, Bennett DA, De Jager PL et al.. bioRxiv, 2026-09-23
Topic: Genetics and APOE
Immunofluorescence staining of FFPE tissue following Xenium processing also preserves cellular morphology, allowing the morphological complexity of distinct cell types to be captured and quantitated, especially for glial cells with highly ramified processes. To demonstrate the practical application of this workflow to AD studies, we developed a proof-of-concept deep learning framework to classify nuclei into specific major cell types of the brain using the IF data. Thus, we present an integrated experimental and analytic workflow optimized for the multi-omic characterization of human brain tissue in an AD context; these pipelines provide spatially resolved insights into pathological microenvironments found in the older human brain and can readily be adjusted to detect other proteins of interest or other pathological features. Altogether, this approach provides a comprehensive view of spatial architecture within pathologically affected regions and enables accurate transcript-independent cell-type annotation. Highlights Integrate Xenium and 4i to build a multi-omic map on the same FFPE brain tissue Improvement of cell-type annotation Identify pathologic features and cross-register them into the transcriptomic and proteomic spatial matrix
Key findings
- Immunofluorescence staining of FFPE tissue following Xenium processing also preserves cellular morphology, allowing the morphological complexity of distinct cell types to be captured and quantitated, especially for glial cells with highly ramified processes.
- To demonstrate the practical application of this workflow to AD studies, we developed a proof-of-concept deep learning framework to classify nuclei into specific major cell types of the brain using the IF data.
- Thus, we present an integrated experimental and analytic workflow optimized for the multi-omic characterization of human brain tissue in an AD context; these pipelines provide spatially resolved insights into pathological microenvironments found in the older human brain and can readily be adjusted to detect other proteins of interest or other pathological features.
- Altogether, this approach provides a comprehensive view of spatial architecture within pathologically affected regions and enables accurate transcript-independent cell-type annotation.
- Highlights Integrate Xenium and 4i to build a multi-omic map on the same FFPE brain tissue Improvement of cell-type annotation Identify pathologic features and cross-register them into the transcriptomic and proteomic spatial matrix
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Study details
- Evidence strengthLow
How this study scored 16/100
Preprint — not yet peer-reviewed. It scored 21 on the same rubric, but non-peer-reviewed sources are capped at 16, so it shows as 16. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it. We have no data on times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record and multi-centre collaboration, so those were left out: it earned 13 of the 62 points we could judge it on, which is 21 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 2 / 10 | Tier 4 — not a peer-reviewed journal (bioRxiv) |
| Journal's citation record | 0 / 4 | Not a journal article, so the journal's record does not count |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 4 / 10 | Preprint — not yet peer-reviewed. Hosted on a preprint server. |
| How recent | 5 / 5 | 2026 — within 1 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | — / 6 | Not yet checked against this library's citation graph — left out of this score |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 1 / 2 | Not in PubMed, but has a DOI |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Points | 13 / 62 | Scored on 12 of 20 parts. We have no data for the rest, so they are left out: 13 of the 62 points we could judge it on is 21 out of 100. |
| Total | 21 / 100 | Capped to 16 because this is not a peer-reviewed article. |
What each of these 20 components measures, and what this score is not →
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Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.
APA 7th
Karaahmet, B., Lama, T., Wang, A., Cao, W., Menon, V., Klein, H., et al. (2026). High-Dimensional Multi-Omic Mapping of Post-Mortem Human Brain Using Iterative Indirect Immunofluorescence Imaging on Xenium-Processed Tissues. bioRxiv. https://doi.org/10.64898/2026.09.16.751033
Vancouver
Karaahmet B, Lama T, Wang A, Cao W, Menon V, Klein H, et al. High-Dimensional Multi-Omic Mapping of Post-Mortem Human Brain Using Iterative Indirect Immunofluorescence Imaging on Xenium-Processed Tissues. bioRxiv. 2026. doi:10.64898/2026.09.16.751033.
BibTeX
@article{karaahmet2026-ff0d1134,
author = {Karaahmet, B. and Lama, T. and Wang, A. and Cao, W. and Menon, V. and Klein, H. and Bennett, D. A. and De Jager, P. L. and others},
title = {{High-Dimensional Multi-Omic Mapping of Post-Mortem Human Brain Using Iterative Indirect Immunofluorescence Imaging on Xenium-Processed Tissues}},
journal = {bioRxiv},
year = {2026},
doi = {10.64898/2026.09.16.751033},
url = {https://doi.org/10.64898/2026.09.16.751033}
}
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