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Alexander Neumann @alexander-neumann.bsky.social · 17/05/2025

Indeed, getting flooded with review request for 2-sample MR papers. To plays devil's advocate: Maybe it's ok/efficient to pump out mindlessly tons of MR papers as long as methods/results are valid? Many are flawed, but many seem scientifically ok, so maybe does not hurt to have it in the literature?

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Reposted by Alexander Neumann

Julia M. Rohrer @dingdingpeng.the100.ci · 11/05/2025

Thanks to everybody who chimed in! I arrived at the conclusion that (1) there's a lot of interesting stuff about interactions and (2) the figure I was looking for does not exist. So, I made it myself! Here's a simple illustration of how to control for confounding in interactions:>

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Alexander Neumann @alexander-neumann.bsky.social · 05/05/2025

What surprised me is how little DNA methylation associations correlated between time points. We found more correlations between different outcomes than between time points. However, a limitation is that this may partly reflect tissue differences (cord blood vs peripheral blood).

Correlations between DNAm effects at birth and childhood and across outcomes. This correlation matrix displays Spearman correlations between regression coefficients for DNAm at birth and childhood and across outcomes. Intensity of red represents higher positive correlations and blue lower negative correlations

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Alexander Neumann @alexander-neumann.bsky.social · 05/05/2025

1. DNA methylation was more strongly associated with child health outcomes when both were measured concurrently in childhood. 2. However, the number of significantly associated DNA methylation sites was not necessarily larger, sometimes even higher when DNA methylation was measured at birth!

Mean effect sizes and statistical significance for DNAm at birth and in childhood. Mean effect sizes (left column) and mean statistical significance (right column) across all tested autosomal DNAm sites per outcome (color) and timepoint. Effect size is given as absolute regression coefficient (|‾β|), representing the difference in child health outcomes in SD between full or no methylation in the case of continuous outcomes (ADHD, general psychopathology, sleep duration, and BMI), or log(odds ratio) for categorical outcomes (asthma diagnosis). Statistical significance is given as mean absolute Z-values

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