基因组生物标志物可以提供一个更深入的理解的重复性压力损伤
Letitia Y Graves1, Katelyn R Schwartz, Josie Shiff
1Letitia Y. Graves, PhD, RN, is Assistant Professor, School of Nursing, University of Texas Medical Branch, Galveston, Texas, and Research Health Scientist, Louis Stokes Cleveland Veterans Affairs Medical Center. Katelyn R. Schwartz, MPH, BSN, RN, is Research Nurse, Cleveland VA Medical Center, Cleveland, Ohio. Josie Shiff, MS, is Research Assistant, Cleveland VA Medical Research & Education Foundation. Ernest R. Chan, PhD, is Research Scientist, Case Western Reserve University, Cleveland. Marinella Galea, MD, is Chief, Spinal Cord Injuries and Disorders, James J. Peters VAMC, Bronx, New York, and Associate Professor, Department of Rehabilitation and Human Performance, Icahn School of Medicine at Mount Sinai, New York. Mary K. Henzel, MD, PhD, is Assistant Chief, Spinal Cord Injuries and Disorders, and Spinal Cord Injury Physiatrist, Louis Stokes Cleveland VA Medical Center. Christine Olney, PhD, RN, is Nurse Scientist, Minneapolis VA Health Care System, Minneapolis, Minnesota. Kath M. Bogie, DPhil, FAIMBE, is Research Career Scientist, Louis Stokes Cleveland Veterans Affairs Medical Center, and Professor, Department of Orthopedics, Case Western Reserve University.
遗传生物标志物可能有助于预测脊髓损伤 (SCI) 患者的复发性压力损伤 (PI). 研究结果表明,脂肪酸代谢和免疫路径的改变与PI风险有关.
科学领域:
- 基因组学就是基因组学.
- 生物标志物发现发现
- 脊髓损伤研究 脊髓损伤研究
背景情况:
- 经常性压力损伤 (PI) 是脊髓损伤 (SCI) 患者的重要并发症.
- 识别具有PIs高风险的个人对于有效的管理和预防策略至关重要.
研究的目的:
- 为了确定基因生物标志物,这些基因生物标志物会使SCI患者更容易患上复发性PI.
- 探索SCI群体中遗传变异,代谢途径和PI风险之间的关系.
主要方法:
- 整个基因组测序和RNA测序是在2至4年内从SCI的退伍军人身上采集的血液样本上进行的.
- 收集了与PI史有关的临床,人口和健康因素.
- 用基因组丰富分析来识别丰富的途径.
主要成果:
- 全基因组测序确定了260个与PI风险增加相关的基因,特别是那些参与脂肪酸代谢的基因.
- 基因组丰富分析显示,脂肪酸代谢途径的丰富程度显著 (P < .01).
- RNA测序显示了高调的生物衰老和低调的抗微生物保护途径.
结论:
- 基因组生物标志物与电子健康记录一起,可以帮助管理SCI患者的复发性PI.
- 这些发现可能使有针对性的干预措施更好地对高风险个体进行表型分组.
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