Spatial clustering of amyotrophic lateral sclerosis in Sardinia, Italy: The contribution of age, sex, and genetic factors

肌萎缩侧索硬化 C9orf72 入射(几何) 人口学 人口 星团(航天器) TARDBP公司 风险因素 生物 遗传学 医学 内科学 等位基因 疾病 SOD1 三核苷酸重复扩增 基因 物理 社会学 计算机科学 光学 程序设计语言
作者
Giuseppe Borghero,Maria Margherita Sechi,Rosario Vasta,Vincenzo Pierri,Francesca Pili,Ida Pateri,Silvy Pilotto,Tommaso Ercoli,Antonella Muroni,Adriano Chiò,Giovanni Defazio
出处
期刊:Muscle & Nerve [Wiley]
卷期号:68 (3): 323-328 被引量:3
标识
DOI:10.1002/mus.27939
摘要

Several microgeographic clusters of higher/lower incidence of amyotrophic lateral sclerosis (ALS) have been identified worldwide. Differences in the distribution of local factors were proposed to explain the excess ALS risk, whereas the contribution of known genetic/epigenetic factors remains unclear. The aim is to identify restricted areas of higher risk in Sardinia and to assess whether age, sex, and the most common causative genetic mutations in Sardinia (C9orf72 and TARDBP mutations) contributed to the variation in the ALS risk.We performed an ad hoc analysis of the 10-y population-based incident cohort of ALS cases from a recent study of a large Sardinian area. Cluster analysis was performed by age- and sex-adjusted Kulldorff's spatial scan statistic.We identified a statistically significant cluster of higher ALS incidence in a relatively large area including 34 municipalities and >100,000 individuals. The investigated genetic mutations were more frequent in the cluster area than outside. Regardless of the genetic mutations, the excess of ALS risk was significantly associated with either sex or with age ≥ 65 y. Finally, an additive interaction between older age and male sex contributed to the excess of ALS risk in the cluster area but not outside.Our analysis demonstrated that known genetic factors, age, and sex may contribute to microgeographic variation in ALS incidence. The significant additive interaction between older age and male sex we found in the high-incidence cluster could suggest the presence of a third factor connecting the analyzed risk factors.
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