Multiple sclerosis risk factors contribute to onset heterogeneity
Multiple sclerosis risk factors contribute to onset heterogeneity
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DOI：
10.1016/j.msard.2018.12.007
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发表时间：
2019-02-01
影响因子：
4
通讯作者：
Ontaneda, Daniel
中科院分区：
文献类型：
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作者：
Briggs, Farren B. S.;Yu, Justin C.;Ontaneda, Daniel
背景：多发性硬化症(MS)的表型表现可预测长期预后，但对MS发病时的异质性因素知之甚少。考虑到临时性，多发性硬化症的危险因素可能也会影响疾病在发病前的表现。方法：通过对多发性硬化症患者的回顾性横断面研究，我们调查了：发病年龄(AOO)、受损功能域(NIFD)、二次复发时间(TT2R)和早期复发活动(ERA)。对每个结果的流行病学数据应用机器学习变量选择，然后是多变量回归模型。这些模型进一步调整了人类白细胞抗原-DRB1*15：01携带者状态和多发性硬化遗传风险评分(GRS)。结果：HLA-DRB1*15：01、GRS和吸烟与早期AOO相关。男性、肥胖、受教育程度低或患有原发进展性多发性硬化症的患者发病时年龄较大。对于NIFD，复发缓解期MS和SES较低的患者NIFD增加。在复发缓解病例中，发病年龄较大、肥胖和多灶性表现的患者TT2R较短，而发病年龄较小和肥胖的患者ERA较大。结论：年龄、遗传特征、肥胖和吸烟状况等个体特征导致疾病表现的异质性，并调节早期病程演变。
Background: The phenotypic presentation of multiple sclerosis (MS) may predict long-term outcomes and little is known about factors contributing to heterogeneity at MS onset. Given temporality, it is likely MS risk factors also influence presentation of the disease near onset.Methods: Using a retrospective cross-sectional study of MS cases, we investigated: age of onset (AOO), number of impaired functional domains (NIFDs), time to second relapse (TT2R), and early relapse activity (ERA). Machine learning variable selection was applied to epidemiologic data for each outcome, followed by multivariable regression models. The models were further adjusted for HLA-DRB1*15:01 carrier status and a MS genetic risk score (GRS). The TT2R and ERA analyses were restricted to relapsing remitting MS cases.Results: HLA-DRB1*15:01, GRS, and smoking were associated with earlier AOO. Cases who were male, obese, had lower education, or had primary progressive MS were older at onset. For NIFDs, those with relapsing remitting MS and of lower SES had increased NIFDs. Among relapsing remitting cases, those who were older at onset, obese, and had polyfocal presentation had shorter TT2R, while ERA was greater among those younger at onset and who were obese.Conclusion: Individual characteristics including age, genetic profiles, obesity, and smoking status contribute to heterogeneity in disease presentation and modulate early disease course evolution.