@tamar_sofer at lunch: "Do gene-environment interactions really exist?" A year later, we've collected our thoughts on mechanisms that produce a detectable GxE and when we might care: https://t.co/0kxvsbcGax
Compliments/criticisms/personal attacks welcome!
Thanks to the many co-authors and TOPMed contributors (including @Riudecanyenc, @deirdre_tobias, and @AlisaManningPhD), and I'd love to hear any feedback and suggestions for future work!
Our gene-macronutrient interaction manuscript is out in Diabetes! https://t.co/XZ2GOOKPB4
We set out to find instances of genetic modification of the relationship between dietary macronutrients and glycemia.
We report: some genetic discovery, some thoughts on statistical power grounded in realistic estimates of diet-related effect sizes and measurement error, and a model for integrating best practices from genetic epidemiology, interaction analysis, and nutritional epidemiology.
Can genetic heritability act as an unbiased metric to compare different phenotype processing methods? Check out our (@kewesterman@AlisaManningPhD et al) latest work applying this to my favorite phenotype (messy diet data).
https://t.co/4XOzR4p4RN
Thrilled to share that our manuscript on T2D genetic clustering is now published!
Soft clustering analysis of type 2 diabetes loci identifies ten physiologically interpretable genetic clusters associated with distinct tissues and clinical outcomes.
https://t.co/gUlJT240qb
But in seriousness, I hope this work encourages discussion about statistical power for gene-diet (and generally, GxE) interactions. Our power calcs here depend substantially on parameter assumptions; what interaction effect sizes are (1) realistic, and (2) practically relevant?
I won't go full tweetorial while on vacation, but check out our new preprint! https://t.co/DSq8sI3O8s
If you like carbohydrates and/or sobering power calculations, this one's for you!
@doctorveera @jacobjchr Our investigation of this isn't published, but was related to what became the triglyceride vignette here: https://t.co/SeSiEXMSej
The idea of TM6SF2 pleiotropy in genetic effects has been described though, for example: https://t.co/xC0AdOqMmi
Shout-out to co-authors @JBCole150, @AlisaManningPhD, @miriam_udler, and others.
You can browse and download our catalog of vQTLs and GxEs on the @AMP_CMDKP (https://t.co/UL7tyXjNJY) -- let us know what you think!
2) We additionally tested for GxEs across all main-effect loci (not just vQTLs), showing that loci with vQTLs were much more enriched for underlying GxEs than standard GWAS loci. This finding supports the original motivation for this project and agrees with existing literature.
@jacobjchr @KCKlatt@sguyenet We've used a PCA-based method to generate a specific number of "effective" tests to use for Bonferroni correction -- see Methods section here: https://t.co/l1i73vy2fU