Department of Neurology
Genetic Phenomena | Genetics | Genomics | Nervous System Diseases
The most recent genome-wide association study in amyotrophic lateral sclerosis (ALS) demonstrates a disproportionate contribution from low-frequency variants to genetic susceptibility of disease. We have therefore begun Project MinE, an international collaboration that seeks to analyse whole-genome sequence data of at least 15,000 ALS patients and 7,500 controls. Here, we report on the design of Project MinE and pilot analyses of newly whole-genome sequenced 1,264 ALS patients and 611 controls drawn from the Netherlands. As has become characteristic of sequencing studies, we find an abundance of rare genetic variation (minor allele frequency < 0.1%), the vast majority of which is absent in public data sets. Principal component analysis reveals local geographical clustering of these variants within The Netherlands. We use the whole-genome sequence data to explore the implications of poor geographical matching of cases and controls in a sequence-based disease study and to investigate how ancestry-matched, externally sequenced controls can induce false positive associations. Also, we have publicly released genome-wide minor allele counts in cases and controls, as well as results from genic burden tests.
genetics, Project MinE, genome sequencing, ALS, amyotrophic lateral sclerosis, The Netherlands
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The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It is made available under a CC-BY-ND 4.0 International license.
DOI of Published Version
bioRxiv 152553; doi: https://doi.org/10.1101/152553. Link to preprint on bioRxiv service.
Project MinE Consortium, Van Rheenen W, Kenna KP, Landers JE, Veldink JH. (2017). Project MinE: study design and pilot analyses of a large-scale whole-genome sequencing study in amyotrophic lateral sclerosis. University of Massachusetts Medical School Faculty Publications. https://doi.org/10.1101/152553. Retrieved from https://escholarship.umassmed.edu/faculty_pubs/1533
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This work is licensed under a Creative Commons Attribution-No Derivative Works 4.0 License.