Genetic and Genomic Medicine

Estimating bone marrow adiposity from head MRI and identifying its genetic architecture

1. Tobias Kaufmann
2. Pål Marius Bjørnstad
3. Martin Falck
4. Stener Nerland
5. Kevin O'Connell
6. Oleksandr Frei
7. Ole A Andreassen
8. Lars T Westlye
9. Srdjan Djurovic
10. Timothy Hughes

• Curated by eLife

  eLife Assessment

  This study introduces an artificial-intelligence tool that estimates fat in skull bone marrow from routine brain scans, enabling large studies that were previously impractical. The evidence for the method's repeatability and for identifying genetic links is convincing overall. The authors identify genes, diseases, and other biological characteristics that are linked to skull marrow fat, which represents an important advance. The work will be of most interest to researchers using large imaging biobanks and those studying ageing-related changes across bone, blood, and brain.

Reviewed by eLife

Design and validation of a clinical whole genome sequencing-based assay for patient screening in a large healthcare system

1. Josiah T. Wagner
2. John T. Welle
3. Isabelle A. Lucas Beckett
4. Kate R. Emery
5. Benjamin A. Cosgrove
6. Krzysztof Olszewski
7. Nick Wagner
8. Tucker C. Bower
9. Li Chi Yuan
10. Eric M. Shull
11. Kathleen Jade
12. Jon Clemens
13. Andrew T. Magis
14. Mary B. Campbell
15. Ora K. Gordon
16. Carlo B. Bifulco
17. Brian D. Piening

Reviewed by PREreview

Functional Effect Predictions For Ion Channel Missense Variants Using a Protein Language Model

1. Sean Gies
2. Artoghrul Alishbayli
3. Paul H.E. Tiesinga
4. Marijn B. Martens

Reviewed by PREreview

Interactions with polygenic background impact quantitative traits in the UK Biobank

1. Lino A. F. Ferreira
2. Sile Hu
3. Robert W. Davies
4. Simon R. Myers

Reviewed by Arcadia Science

Genomic privacy risks in GWAS summary statistics

1. Ao Lan
2. Yudi Pawitan
3. Xia Shen

• Curated by eLife

  eLife Assessment

  This important study provides a theoretical framework for quantifying privacy risk from publicly shared genome-wide association summary statistics. The findings reveal the conditions under which genotype reconstruction may become feasible, challenging long-held assumptions about personal data safety. While the evidence is solid, supported by clear mathematical derivations and simulations, validation on large empirical datasets would further strengthen the claims.

Reviewed by eLife

Monocyte-endothelial interactions as a targetable node in clonal hematopoiesis-mediated cardiovascular disease

1. Alyssa C Parker
2. J Brett Heimlich
3. Joseph C Van Amburg
4. Yash Pershad
5. David A Ong
6. Nicole A Mickels
7. Laventa M Obare
8. Ketan J Hoey
9. Hannah K Giannini
10. Ayesha Ahmad
11. Caitlyn Vlasschaert
12. Tarak N Nandi
13. Ravi K Madduri
14. Samuel S Bailin
15. John R Koethe
16. Celestine N Wanjalla
17. Alexander G Bick

• Curated by eLife

  eLife Assessment

  Clonal hematopoiesis of indeterminate potential (CHIP) is a known risk factor for coronary artery disease, though its precise role in disease progression continues to emerge. This study leverages valuable single-cell RNA data from patients with CHIP mutations and controls to predict key interactions between endothelial cells and monocytes. Using an AI prediction model, the authors identify druggable targets that mediate immune cell interactions in CHIP and provide solid evidence to support their findings.

Reviewed by eLife