University of Massachusetts Medical School Faculty Publications

UMMS Affiliation

Department of Neurology

Publication Date

6-20-2017

Document Type

Article Preprint

Disciplines

Genetic Phenomena | Genetics | Genomics | Nervous System Diseases

Abstract

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.

Keywords

genetics, Project MinE, genome sequencing, ALS, amyotrophic lateral sclerosis, The Netherlands

Rights and Permissions

The copyright holder for this preprint (which was not peer-reviewed) is the author/funder.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

10.1101/152553

Source

bioRxiv 152553; doi: https://doi.org/10.1101/152553. Link to preprint on bioRxiv service.

Comments

Full author list omitted for brevity. For the full list of authors, see article.

Journal/Book/Conference Title

bioRxiv

Creative Commons License

Creative Commons Attribution-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-No Derivative Works 4.0 License.

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