研究利用头部 MRI 估算颅骨骨髓脂肪并解析其遗传结构
Estimating bone marrow adiposity from head MRI and identifying its genetic architecture
研究团队开发人工神经网络，在 T1 加权头部 MRI 中定位颅骨骨髓，从而在多个大型 MRI 数据集中估算其脂肪组成，并建模性别二态的年龄轨迹，包括绝经的影响。基于单核苷酸多态性与双生子数据，该性状表现出高遗传力，研究识别出 41 个显著相关遗传位点，其中 6 个具有性别特异性。将定位到的基因与已有骨髓单细胞 RNA-seq 数据整合，揭示了脂肪谱系分化与脂质负载的模式。研究还发现该性状与认知能力和帕金森病等人类性状存在显著遗传相关，作者认为这与近期发现的连接颅骨骨髓与脑膜的通道相呼应。
来源：eLife · doi.org
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.