Ran S Rotem, Andrea Bellavia, Sabrina Paganoni, Marc G Weisskopf
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引用次数: 0
摘要
背景:越来越多的证据表明,非遗传因素在肌萎缩性脊髓侧索硬化症(ALS)中起着重要的致病作用,然而确定具体的罪魁祸首却一直具有挑战性。许多药物以与 ALS 发病机制有关联的生物通路为靶点,对大型药理学数据集进行信号筛选可大大加快 ALS 风险调节药理学因素的鉴定:我们采用基于梯度提升决策树的先进机器学习方法,结合贝叶斯模型优化和重复数据采样,对患者的用药史和 ALS 风险进行了高维筛查。研究人员从以色列一家大型医疗基金获得了501例ALS病例和4998例匹配对照的临床和配药数据,并在确诊ALS前滞后3年或5年确定药物接触情况:在 1000 多种不同的药物中,我们发现有 8 种药物在独立训练的模型中始终与 ALS 风险增加相关,其中大多数药物用于控制与 ALS 有关的症状。我们还观察到一些提示性的保护作用,尤其是维生素 E:我们的研究结果表明,在公认的前驱期之前服用某些药物与 ALS 风险有关。这可能是因为这些药物增加了 ALS 的风险,也可能表明 ALS 症状可能早在前驱期之前就已显现。研究结果还进一步证明,维生素 E 可能是 ALS 的保护因素。应开展有针对性的研究,以阐明可能的病理生理机制,同时为治疗方法的设计提供启示。
Medication use and risk of amyotrophic lateral sclerosis: using machine learning for an exposome-wide screen of a large clinical database.
Background: Accumulating evidence suggests that non-genetic factors have important etiologic roles in amyotrophic lateral sclerosis (ALS), yet identification of specific culprit factors has been challenging. Many medications target biological pathways implicated in ALS pathogenesis, and screening large pharmacologic datasets for signals could greatly accelerate the identification of risk-modulating pharmacologic factors for ALS.
Method: We conducted a high-dimensional screening of patients' history of medication use and ALS risk using an advanced machine learning approach based on gradient-boosted decision trees coupled with Bayesian model optimization and repeated data sampling. Clinical and medication dispensing data were obtained from a large Israeli health fund for 501 ALS cases and 4,998 matched controls using a lag period of 3 or 5 years prior to ALS diagnosis for ascertaining medication exposure.
Results: Of over 1,000 different medication classes, we identified 8 classes that were consistently associated with increased ALS risk across independently trained models, where most are indicated for control of symptoms implicated in ALS. Some suggestive protective effects were also observed, notably for vitamin E.
Discussion: Our results indicate that use of certain medications well before the typically recognized prodromal period was associated with ALS risk. This could result because these medications increase ALS risk or could indicate that ALS symptoms can manifest well before suggested prodromal periods. The results also provide further evidence that vitamin E may be a protective factor for ALS. Targeted studies should be performed to elucidate the possible pathophysiological mechanisms while providing insights for therapeutics design.