Division of Neuroimmunology and Neurological Infections, Department of Neurology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
Ann Neurol. 2022 Oct;92(4):688-698. doi: 10.1002/ana.26446. Epub 2022 Jul 13.
To assess the effects of demographics, lifestyle factors, and comorbidities on serum neurofilament light chain (sNfL) levels in people without neurologic disease and establish demographic-specific reference ranges of sNfL.
The National Health and Nutrition Examination Survey (NHANES) is a representative sample of the US population in which detailed information on demographic, lifestyle, routine laboratory tests, and overall health status are systematically collected. From stored serum samples, we measured sNfL levels using a novel high-throughput immunoassay (Siemens Healthineers). We evaluated the predictive capacity of 52 demographic, lifestyle, comorbidity, anthropometric, or laboratory characteristics in explaining variability in sNfL levels. Predictive performance was assessed using cross-validated R (R ) and forward selection was used to obtain a set of best predictors of sNfL levels. Adjusted reference ranges were derived incorporating characteristics using generalized additive models for location, scale, and shape.
We included 1,706 NHANES participants (average age: 43.6 ± 14.8 y; 50.6% male, 35% non-white) without neurological disorders. In univariate models, age explained the most variability in sNfL (R = 26.8%). Multivariable prediction models for sNfL contained three covariates (in order of their selection): age, creatinine, and glycosylated hemoglobin (HbA1c) (standardized β-age: 0.46, 95% confidence interval [CI]: 0.43, 0.50; creatinine: 0.18, 95% CI: 0.13, 0.22; HbA1c: 0.09, 95% CI: 0.06, 0.11). Adjusted centile curves were derived incorporating identified predictors. We provide an interactive R Shiny application to translate our findings and allow other investigators to use the derived centile curves.
Results will help to guide interpretation of sNfL levels as they relate to neurologic conditions. ANN NEUROL 2022;92:688-698.
评估人口统计学、生活方式因素和合并症对无神经疾病人群血清神经丝轻链（sNfL）水平的影响，并建立 sNfL 的人口统计学特异性参考范围。
国家健康和营养检查调查（NHANES）是美国人口的代表性样本，系统收集了人口统计学、生活方式、常规实验室检查和整体健康状况的详细信息。我们使用新型高通量免疫测定法（西门子健康公司）从储存的血清样本中测量 sNfL 水平。我们评估了 52 个人口统计学、生活方式、合并症、人体测量或实验室特征对 sNfL 水平变异性的预测能力。使用交叉验证 R（R）评估预测性能，并使用向前选择获得一组 sNfL 水平的最佳预测因子。使用广义加性模型对位置、比例和形状进行调整，得出包含特征的调整参考范围。
我们纳入了 1706 名无神经疾病的 NHANES 参与者（平均年龄：43.6±14.8y；50.6%为男性，35%为非白人）。在单变量模型中，年龄解释了 sNfL 最大的变异性（R ²=26.8%）。sNfL 的多变量预测模型包含三个协变量（按选择顺序）：年龄、肌酐和糖化血红蛋白（HbA1c）（标准化β-年龄：0.46，95%置信区间[CI]：0.43，0.50；肌酐：0.18，95% CI：0.13，0.22；HbA1c：0.09，95% CI：0.06，0.11）。纳入确定的预测因子后，我们得出了调整后的百分位数曲线。我们提供了一个交互式 R Shiny 应用程序，以翻译我们的发现，并允许其他研究人员使用衍生的百分位数曲线。
这些结果将有助于指导解释 sNfL 水平与神经状况的关系。
