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The power to detect disease associations with mitochondrial DNA haplogroups

Lookup NU author(s): Dr David Samuels, Dr Robin Horton, Professor Patrick Chinnery

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Abstract

Genetic variation of mitochondrial DNA (mtDNA) has been linked to a number of multifactorial diseases, but there is currently no tool available to predict the optimal size for these investigations. We used a simulation-based (Monte Carlo) permutation test to generate power curves for European mtDNA haplogroup studies, to derive a universal equation to enable power calculations for prospective studies across the globe, and to show that very large cohorts are required to reliably detect an association with complex human diseases. In some populations, geographical variation in haplogroup frequencies will prevent the reliable detection of subtle haplogroup associations with uncommon disorders. © 2006 by The American Society of Human Genetics. All rights reserved.

Publication metadata

Author(s): Samuels DC, Carothers AD, Horton R, Chinnery PF

Publication type: Article

Publication status: Published

Journal: American Journal of Human Genetics

Year: 2006

Volume: 78

Issue: 4

Pages: 713-720

ISSN (print): 0002-9297

ISSN (electronic): 1537-6605

Publisher: Cell Press

URL: http://dx.doi.org/10.1086/502682

DOI: 10.1086/502682

PubMed id: 16532401

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