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Linda Kvastad

@kvastad.bsky.social

69 followers 110 following 13 posts

PostDoc at Karolinska Institutet, Department of Cell and Molecular Biology. Spatial transcriptomics science adventures! "Well-being and mental health skills are human rights & of monumental importance to scientific excellence" @csi-initiative.bsky.social

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Linda Kvastad @kvastad.bsky.social · May 22

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

Linda Kvastad @kvastad.bsky.social · May 22

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

Linda Kvastad @kvastad.bsky.social · May 22

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.

Linda Kvastad @kvastad.bsky.social · May 22

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

Linda Kvastad @kvastad.bsky.social · May 22

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.

Linda Kvastad @kvastad.bsky.social · May 22

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

Linda Kvastad @kvastad.bsky.social · May 22

🫀 Coronary artery disease → Enrichment in heart vessels.

Linda Kvastad @kvastad.bsky.social · May 22

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

Linda Kvastad @kvastad.bsky.social · May 22

🧮 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.

Linda Kvastad @kvastad.bsky.social · May 22

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

Linda Kvastad @kvastad.bsky.social · May 22

🚀 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.

Linda Kvastad @kvastad.bsky.social · May 22

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

Linda Kvastad @kvastad.bsky.social · May 6

Thank you Embla ❤️

Reposted by Linda Kvastad

Tuuli Lappalainen @tuuliel.bsky.social · May 5

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...

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...

www.biorxiv.org