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This article is part of the supplement: Genetic Analysis Workshop 17: Unraveling Human Exome Data

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Mutational load analysis of unrelated individuals

Daniel P Howrigan12*, Matthew A Simonson12, Helen M Kamens13, Sarah H Stephens13, Amanda G Wills12, Marissa A Ehringer13, Matthew C Keller12 and Matthew B McQueen13

Author Affiliations

1 Institute for Behavioral Genetics, University of Colorado at Boulder, 1480 30th Street, Boulder, CO 80303, USA

2 Department of Psychology, University of Colorado at Boulder, 345 UCB, Boulder, CO 80309-0345, USA

3 Department of Integrative Physiology, University of Colorado at Boulder, Clare Small 113, 354 UCB, Boulder, CO 80309-0354, USA

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BMC Proceedings 2011, 5(Suppl 9):S55  doi:10.1186/1753-6561-5-S9-S55

Published: 29 November 2011


Evolutionary genetic models predict that the cumulative effect of rare deleterious mutations across the genome—known as mutational load burden—increases the susceptibility to complex disease. To test the mutational load burden hypothesis, we adopted a two-tiered approach: assessing the impact of whole-exome minor allele load burden and then conducting individual-gene screening. For our primary analysis, we examined various minor allele frequency (MAF) thresholds and weighting schemes to examine the overall effect of minor allele load on affection status. We found a consistent association between minor allele load and affection status, but this effect did not markedly increase within rare and/or functional single-nucleotide polymorphisms (SNPs). Our follow-up analysis considered minor allele load in individual genes to see whether only one or a few genes were driving the overall effect. Examining our most significant result—minor allele load of nonsynonymous SNPs with MAF < 2.4%—we detected no significantly associated genes after Bonferroni correction for multiple testing. After moderately significant genes (p < 0.05) were removed, the overall effect of rare nonsynonymous allele load remained significant. Overall, we did not find clear support for mutational load burden on affection status; however, these results are ultimately dependent on and limited by the nature of the Genetic Analysis Workshop 17 simulation.