💊 Spatial coexpression of disease genes in enriched structures suggests a new avenue:
→ Spatially informed drug repurposing strategies.

🧠 Top Alzheimer’s genes, identified with STEAM, were enriched among upregulated DEGs in specific cell types—Microglia showing the strongest signal.

In sc/snRNAseq from brain we found enrichment for Alzheimer’s pointing towards immune and barrier dysfunction. Here using a sliding window approach to enrichment, scanning through the ranked gene list of genetically associated genes.

In the pancreas, we saw reorganization of disease-relevant cell types for type 1 diabetes—implicating both endocrine & exocrine compartments.

In developing human spinal cord, we found anterior horn disorder enriched in ventral horn grey matter— this pattern was consistent across multiple developmental time points.

Chronic kidney disease → Enrichment in proximal tubule & glomerulus.
🔄 These two structures are known to engage in crosstalk: damage to one can affect the other.

🫀 Coronary artery disease → Enrichment in heart vessels.

📊 Up to 20% of trait-tissue pairs show structure-specific enrichment — reinforcing the power of spatial resolution.

🧮 For ranked gene lists, STEAM uses a sliding window to compare signal vs. null distribution — finding sets of top enriched genes.
💡 We used @opentargets.org for curated gene lists with genetic associations.

🔬 Study scale:
• 8 organs
• 31 spatial datasets
• 32 human diseases
• 152 trait-tissue pairs
• 2 brain sc/snRNA-seq datasets

🚀 New method: Identify putative causal tissue structures and cell types for complex traits using your Seurat object + a ranked gene list.
🧰 Our tool: the upcoming R package STEAM.

Recently presented our work on how spatial transcriptomics + genetics can reveal putative causal tissue structures for complex traits.
📄 Preprint: doi.org/10.1101/2025...
#spatialbiology #genomics #genetics @lifesciences-ge.bsky.social

Thank you Embla ❤️

Spatial transcriptomics and genetically implicated genes identify putative causal tissue structures for complex traits Spatially resolved transcriptomics is transforming our understanding of cellular and molecular diversity of tissues. Here, to identify tissue structures that are enriched for putatively causal disease...

New preprint! My (now former) postdoc @kvastad.bsky.social led this integration of GWAS and spatial transcriptomics (ST) data to identify tissue structures with enrichment of disease-implicated genes = likely causal drivers of disease biology.
www.biorxiv.org/content/10.1...