To identify novel genes associated with ALS, we undertook two lines of investigation. We carried out a genome-wide association study comparing 20,806 ALS cases and 59,804 controls. Independently, we performed a rare variant burden analysis comparing 1,138 index familial ALS cases and 19,494 controls. Through both approaches, we identified kinesin family member 5A (KIF5A) as a novel gene associated with ALS. Interestingly, mutations predominantly in the N-terminal motor domain of KIF5A are causative for two neurodegenerative diseases: hereditary spastic paraplegia (SPG10) and Charcot-Marie-Tooth type 2 (CMT2). In contrast, ALS-associated mutations are primarily located at the C-terminal cargo-binding tail domain and patients harboring loss-of-function mutations displayed an extended survival relative to typical ALS cases. Taken together, these results broaden the phenotype spectrum resulting from mutations in KIF5A and strengthen the role of cytoskeletal defects in the pathogenesis of ALS.
Amyotrophic lateral sclerosis (ALS) is a relatively rare disease with a reported population incidence of between 1.5 and 2.5 per 100,000 per year. Over the past 10 years, the design of ALS epidemiological studies has evolved to focus on a prospective, population based methodology, employing the El Escorial criteria and multiple sources of data to ensure complete case ascertainment. Five such studies, based in Europe and North America, have been published and show remarkably consistent incidence figures among their respective Caucasian populations. Population based studies have been useful in defining clinical characteristics and prognostic indicators in ALS. However, many epidemiological questions remain that cannot be resolved by any of the existing population based datasets. The working hypotheses is that ALS, like other chronic diseases, is a complex genetic condition, and the relative contributions of individual environmental and genetic factors are likely to be relatively small. Larger studies are required to characterise risks and identify subpopulations that might be suitable for further study. This current paper outlines the contribution of the various population based registers, identifies the limitations of the existing datasets and proposes a mechanism to improve the future design and output of descriptive epidemiological studies.
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