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Power and sample size estimation for epigenome-wide association scans to detect differential DNA methylation.

Tsai PC, Bell JT - Int J Epidemiol (2015)

Bottom Line: We performed simulations to estimate power under the case-control and discordant MZ twin EWAS study designs, under a range of epigenetic risk effect sizes and conditions.Our analyses highlighted several factors that significantly influenced EWAS power, including sample size, epigenetic risk effect size, the variance of DNA methylation at the locus of interest and the correlation in DNA methylation patterns within the twin sample.Our results can help guide EWAS experimental design and interpretation for future epigenetic studies.

View Article: PubMed Central - PubMed

Affiliation: Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.

No MeSH data available.


Example of a permutation procedure. Cases were drawn from the case distribution and matched controls, and healthy co-twins were drawn from the control distribution. Only permutations with a set effect size between the two groups were used in the power calculation. The cases are identical for both case-control and twin designs (black dots). Controls in the case-control design were randomly selected from the control distribution. In the twin design, DNA methylation profiles in healthy co-twin controls were correlated with cases (Spearman’s correlation coefficients between 0.193 and 0.616). The thickness of the blue line in the twin design illustrates the similarity in DNA methylation between twins.
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dyv041-F2: Example of a permutation procedure. Cases were drawn from the case distribution and matched controls, and healthy co-twins were drawn from the control distribution. Only permutations with a set effect size between the two groups were used in the power calculation. The cases are identical for both case-control and twin designs (black dots). Controls in the case-control design were randomly selected from the control distribution. In the twin design, DNA methylation profiles in healthy co-twin controls were correlated with cases (Spearman’s correlation coefficients between 0.193 and 0.616). The thickness of the blue line in the twin design illustrates the similarity in DNA methylation between twins.

Mentions: Power was estimated under two EWAS study designs, case-control and disease-discordant monozygotic (MZ) twins. To compare power under the same parameters in the case-control and twin designs, we assumed that cases were identical in both study designs, and their matched controls and unaffected co-twins were sampled from the control distribution. In case-control design, the controls were selected based on the defined effect sizes. In the MZ discordant twin design, unaffected co-twins were selected with additional intra-pair locus-specific correlation. In each simulation, cases were selected from one of the eight Case distributions, and for the disease-discordant MZ twin design unaffected co-twins were sampled from the control distribution if: (i) the mean difference within the co-twins matched the pre-specified effect size; and (ii) the Spearman’s correlation coefficient within MZ pairs was between 0.193 and 0.616, which represented the genome-wide mean correlation coefficients ± 1 SD in a previously published set of 21 MZ twins using Illumina 27K.3 Once MZ twin pairs were selected, for each affected twin (or case) we also sampled a matched healthy unrelated control sample from the control distribution. Figure 2 shows an example simulation procedure by selecting the cases from distribution Case 3 and both matched unrelated controls and matched healthy co-twins from the control distribution.Figure 2.


Power and sample size estimation for epigenome-wide association scans to detect differential DNA methylation.

Tsai PC, Bell JT - Int J Epidemiol (2015)

Example of a permutation procedure. Cases were drawn from the case distribution and matched controls, and healthy co-twins were drawn from the control distribution. Only permutations with a set effect size between the two groups were used in the power calculation. The cases are identical for both case-control and twin designs (black dots). Controls in the case-control design were randomly selected from the control distribution. In the twin design, DNA methylation profiles in healthy co-twin controls were correlated with cases (Spearman’s correlation coefficients between 0.193 and 0.616). The thickness of the blue line in the twin design illustrates the similarity in DNA methylation between twins.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4588864&req=5

dyv041-F2: Example of a permutation procedure. Cases were drawn from the case distribution and matched controls, and healthy co-twins were drawn from the control distribution. Only permutations with a set effect size between the two groups were used in the power calculation. The cases are identical for both case-control and twin designs (black dots). Controls in the case-control design were randomly selected from the control distribution. In the twin design, DNA methylation profiles in healthy co-twin controls were correlated with cases (Spearman’s correlation coefficients between 0.193 and 0.616). The thickness of the blue line in the twin design illustrates the similarity in DNA methylation between twins.
Mentions: Power was estimated under two EWAS study designs, case-control and disease-discordant monozygotic (MZ) twins. To compare power under the same parameters in the case-control and twin designs, we assumed that cases were identical in both study designs, and their matched controls and unaffected co-twins were sampled from the control distribution. In case-control design, the controls were selected based on the defined effect sizes. In the MZ discordant twin design, unaffected co-twins were selected with additional intra-pair locus-specific correlation. In each simulation, cases were selected from one of the eight Case distributions, and for the disease-discordant MZ twin design unaffected co-twins were sampled from the control distribution if: (i) the mean difference within the co-twins matched the pre-specified effect size; and (ii) the Spearman’s correlation coefficient within MZ pairs was between 0.193 and 0.616, which represented the genome-wide mean correlation coefficients ± 1 SD in a previously published set of 21 MZ twins using Illumina 27K.3 Once MZ twin pairs were selected, for each affected twin (or case) we also sampled a matched healthy unrelated control sample from the control distribution. Figure 2 shows an example simulation procedure by selecting the cases from distribution Case 3 and both matched unrelated controls and matched healthy co-twins from the control distribution.Figure 2.

Bottom Line: We performed simulations to estimate power under the case-control and discordant MZ twin EWAS study designs, under a range of epigenetic risk effect sizes and conditions.Our analyses highlighted several factors that significantly influenced EWAS power, including sample size, epigenetic risk effect size, the variance of DNA methylation at the locus of interest and the correlation in DNA methylation patterns within the twin sample.Our results can help guide EWAS experimental design and interpretation for future epigenetic studies.

View Article: PubMed Central - PubMed

Affiliation: Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.

No MeSH data available.