TY  - JOUR
U1  - Wissenschaftlicher Artikel
A1  - Kruppa-Scheetz, Jochen
A1  - Sieg, Miriam
A1  - Richter, Gesa Marijke
A1  - Pohrt, Anne
T1  - Estimands in epigenome-wide association studies
JF  - Clinical Epigenetics
N2  - Background
In DNA methylation analyses like epigenome-wide association studies, effects in differentially methylated CpG sites are assessed. Two kinds of outcomes can be used for statistical analysis: Beta-values and M-values. M-values follow a normal distribution and help to detect differentially methylated CpG sites. As biological effect measures, differences of M-values are more or less meaningless. Beta-values are of more interest since they can be interpreted directly as differences in percentage of DNA methylation at a given CpG site, but they have poor statistical properties. Different frameworks are proposed for reporting estimands in DNA methylation analysis, relying on Beta-values, M-values, or both.

Results
We present and discuss four possible approaches of achieving estimands in DNA methylation analysis. In addition, we present the usage of M-values or Beta-values in the context of bioinformatical pipelines, which often demand a predefined outcome. We show the dependencies between the differences in M-values to differences in Beta-values in two data simulations: a analysis with and without confounder effect. Without present confounder effects, M-values can be used for the statistical analysis and Beta-values statistics for the reporting. If confounder effects exist, we demonstrate the deviations and correct the effects by the intercept method. Finally, we demonstrate the theoretical problem on two large human genome-wide DNA methylation datasets to verify the results.

Conclusions
The usage of M-values in the analysis of DNA methylation data will produce effect estimates, which cannot be biologically interpreted. The parallel usage of Beta-value statistics ignores possible confounder effects and can therefore not be recommended. Hence, if the differences in Beta-values are the focus of the study, the intercept method is recommendable. Hyper- or hypomethylated CpG sites must then be carefully evaluated. If an exploratory analysis of possible CpG sites is the aim of the study, M-values can be used for inference.
KW  - Multiple testing
KW  - DNA methylation
KW  - Reproducible research
KW  - Epigenome-wide association study (EWAS)
KW  - Estimands
Y1  - 2021
UN  - https://nbn-resolving.org/urn:nbn:de:bsz:959-opus-58977
SN  - 1868-7083
SS  - 1868-7083
SN  - 1868-7075
SS  - 1868-7075
U6  - https://doi.org/10.1186/s13148-021-01083-9
DO  - https://doi.org/10.1186/s13148-021-01083-9
IS  - 13
SP  - 16
S1  - 16
ER  -