医学
洛伐他汀
肌萎缩侧索硬化
人口
运动神经元
SOD1
内科学
肿瘤科
药理学
疾病
胆固醇
环境卫生
作者
Collin J. Kreple,Susan Searles Nielsen,Kathleen M. Schoch,Tao Shen,Mark Shabsovich,Yizhe Song,Brad A. Racette,Timothy M. Miller
摘要
Objective The objective of this study was to use a novel combined pharmacoepidemiologic and amyotrophic lateral sclerosis (ALS) mouse model approach to identify potential motor neuron protective medications. Methods We constructed a large, population‐based case‐control study to investigate motor neuron disease (MND) among US Medicare beneficiaries aged 66 to 90 in 2009. We included 1,128 incident MND cases and 56,400 age, sex, race, and ethnicity matched controls. We calculated MND relative risk for >1,000 active ingredients represented in Part D (pharmacy) claims in 2006 to 2007 (>1 year before diagnosis/reference). We then applied a comprehensive screening approach to select medications for testing in SOD1 G93A mice: sulfasalazine, telmisartan, and lovastatin. We treated mice with the human dose equivalent of the medication or vehicle via subcutaneous osmotic pump before onset of weakness. We then assessed weight, gait, and survival. In additional mice, we conducted histological studies. Results We observed previously established medical associations for MND and an inverse dose–response association between lovastatin and MND, with 28% reduced risk at 40 mg/day. In SOD1 G93A mouse studies, sulfasalazine and telmisartan conferred no benefit, whereas lovastatin treatment delayed onset and prolonged survival. Lovastatin treated mice also had less microgliosis, misfolded SOD1, and spinal motor neuron loss in the ventral horn. Interpretation Lovastatin reduced the risk of ALS in humans, which was confirmed in an ALS mouse model by delayed symptom onset, prolonged survival, and preservation of motor neurons. Although further studies to understand the mechanism are required, lovastatin may represent a potential neuroprotective therapy for patients with ALS. These data demonstrate the utility of a combined pharmacoepidemiologic and mouse model approach. ANN NEUROL 2023;93:881–892
科研通智能强力驱动
Strongly Powered by AbleSci AI