Skip to content
DraconiticResearch
Search Sources API
181,713 studies31 sourcesUpdated 35 min ago
Peer-reviewedCC BY 4.0eLife

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

  • Tobias Kaufmann1,2,3
  • Pål Marius Bjørnstad4
  • Martin Falck4
  • Stener Nerland3,5
  • Kevin O'Connell3
  • Oleksandr Frei3,6
  • Ole A Andreassen3,7
  • Lars T Westlye3,7,8
  • Srdjan Djurovic3,4
  • Timothy Hughes3,4
8 affiliations
  1. 1Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health, University of Tübingen, Tübingen, Germany
  2. 2German Center for Mental Health (DZPG), Partner Site Tübingen, Tübingen, Germany
  3. 3Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
  4. 4Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
  5. 5Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
  6. 6Department of Pharmacy, University of Oslo, Oslo, Norway
  7. 7KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
  8. 8Department of Psychology, University of Oslo, Oslo, Norway
Read full textPDFDOICite

Abstract

Bone marrow (BM) adiposity changes radically through the lifespan, but this phenomenon is poorly characterized and understood in humans. Large datasets of magnetic resonance imaging (MRI) scans of the head have been collected to study the human brain, but also contain unexploited information about other organs. We developed an artificial neural network that localizes calvarial BM in T1-weighted MRI head scans, enabling us to study its composition in several large MRI datasets, and to model sex-dimorphic age trajectories, including the effect of menopause. We revealed high heritability in single-nucleotide polymorphism and twin data, and identified 41 genetic loci significantly associated with the trait, including six sex-specific loci. Integrating mapped genes with existing BM single-cell RNA-sequencing data revealed patterns of adipogenic lineage differentiation and lipid loading. Finally, we identified significant genetic correlations with several human traits, including cognitive ability and Parkinson’s disease, which is intriguing in light of the recently discovered channels that link calvarial BM to the meninges.

Related

  1. Identifying the shared genetic architecture among severe COVID-19, type 2 diabetes, and obesity using cross-trait meta-analysis
    Seunghwan Park, Jieun Seo, Taesung Park +1
    Scientific ReportsPeer-reviewedCC BYFull textGenetics & genomicsDOAJ
  2. A genetic anemia disentangles the dual effect of chronically reduced thrombopoietin on hematopoietic stem cells and bone marrow niche
    A. Aprile, A. Malara, M. Storto +12
    bioRxivPreprintAll rights reservedFull textCell biologybioRxiv
  3. sandwrm: An R Package for Estimating Wright's Neighbourhood Size and Species‐Level Genetic Diversity
    Zachary B. Hancock, Gideon S. Bradburd
    Molecular Ecology ResourcesPeer-reviewedCC BY-NC 4.0Full textGenetics & genomicsPMCEurope PMC
  4. Self-supervised representations reveal the genetic architecture of human cortical folding
    Antoine Dufournet, Julien Laval, Joël Chavas +4
    HALPreprintAll rights reservedFull textGenetics & genomicsNeuroscienceHALbioRxiv
  5. Dynamic genetic architecture and integrative association analysis of milk nitrogen traits in primiparous and multiparous Holstein cows
    Hao Zhu, Yu Zhou, Jianing Diao +2
    BMC GenomicsPeer-reviewedCC BY 4.0Genetics & genomicsCrossref

Cite

BibTeXRIS
BibTeX
@article{kaufmann2026estimating,
  title = {{Estimating bone marrow adiposity from head MRI and identifying its genetic architecture}},
  author = {Tobias Kaufmann and Pål Marius Bjørnstad and Martin Falck and Stener Nerland and Kevin O'Connell and Oleksandr Frei and Ole A Andreassen and Lars T Westlye and Srdjan Djurovic and Timothy Hughes},
  journal = {eLife},
  year = {2026},
  month = nov,
  doi = {10.7554/elife.101499},
  url = {https://elifesciences.org/articles/101499},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Estimating bone marrow adiposity from head MRI and identifying its genetic architecture
AU  - Tobias Kaufmann
AU  - Pål Marius Bjørnstad
AU  - Martin Falck
AU  - Stener Nerland
AU  - Kevin O'Connell
AU  - Oleksandr Frei
AU  - Ole A Andreassen
AU  - Lars T Westlye
AU  - Srdjan Djurovic
AU  - Timothy Hughes
PY  - 2026
DA  - 2026/11/04
JO  - eLife
DO  - 10.7554/elife.101499
UR  - https://elifesciences.org/articles/101499
AB  - Bone marrow (BM) adiposity changes radically through the lifespan, but this phenomenon is poorly characterized and understood in humans. Large datasets of magnetic resonance imaging (MRI) scans of the head have been collected to study the human brain, but also contain unexploited information about other organs. We developed an artificial neural network that localizes calvarial BM in T1-weighted MRI head scans, enabling us to study its composition in several large MRI datasets, and to model sex-dimorphic age trajectories, including the effect of menopause. We revealed high heritability in single-nucleotide polymorphism and twin data, and identified 41 genetic loci significantly associated with the trait, including six sex-specific loci. Integrating mapped genes with existing BM single-cell RNA-sequencing data revealed patterns of adipogenic lineage differentiation and lipid loading. Finally, we identified significant genetic correlations with several human traits, including cognitive ability and Parkinson’s disease, which is intriguing in light of the recently discovered channels that link calvarial BM to the meninges.
SN  - 2050-084X
ER  -