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Mutational load analysis of unrelated individuals

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 who...

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Autores principales: Howrigan, Daniel P, Simonson, Matthew A, Kamens, Helen M, Stephens, Sarah H, Wills, Amanda G, Ehringer, Marissa A, Keller, Matthew C, McQueen, Matthew B
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287893/
https://www.ncbi.nlm.nih.gov/pubmed/22373138
http://dx.doi.org/10.1186/1753-6561-5-S9-S55
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author Howrigan, Daniel P
Simonson, Matthew A
Kamens, Helen M
Stephens, Sarah H
Wills, Amanda G
Ehringer, Marissa A
Keller, Matthew C
McQueen, Matthew B
author_facet Howrigan, Daniel P
Simonson, Matthew A
Kamens, Helen M
Stephens, Sarah H
Wills, Amanda G
Ehringer, Marissa A
Keller, Matthew C
McQueen, Matthew B
author_sort Howrigan, Daniel P
collection PubMed
description 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.
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spelling pubmed-32878932012-02-28 Mutational load analysis of unrelated individuals Howrigan, Daniel P Simonson, Matthew A Kamens, Helen M Stephens, Sarah H Wills, Amanda G Ehringer, Marissa A Keller, Matthew C McQueen, Matthew B BMC Proc Proceedings 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. BioMed Central 2011-11-29 /pmc/articles/PMC3287893/ /pubmed/22373138 http://dx.doi.org/10.1186/1753-6561-5-S9-S55 Text en Copyright ©2011 Howrigan et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Proceedings
Howrigan, Daniel P
Simonson, Matthew A
Kamens, Helen M
Stephens, Sarah H
Wills, Amanda G
Ehringer, Marissa A
Keller, Matthew C
McQueen, Matthew B
Mutational load analysis of unrelated individuals
title Mutational load analysis of unrelated individuals
title_full Mutational load analysis of unrelated individuals
title_fullStr Mutational load analysis of unrelated individuals
title_full_unstemmed Mutational load analysis of unrelated individuals
title_short Mutational load analysis of unrelated individuals
title_sort mutational load analysis of unrelated individuals
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287893/
https://www.ncbi.nlm.nih.gov/pubmed/22373138
http://dx.doi.org/10.1186/1753-6561-5-S9-S55
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