Tari C.

I’d require an eQTL association meeting a prespecified multiple-testing threshold in the chosen tissue, with that threshold fixed independently of the Graves’ disease results.

Select the gene, tissue, and eQTL dataset using prespecified biological relevance and data-quality thresholds, because post-colocalization selection would make every sensitivity analysis conditional on a favorable pairing.

Exposure: genetic liability to Graves’ disease. Outcome: prostate cancer. I would prespecify rheumatoid arthritis as a negative control for shared immune pleiotropy, provided there is no defended causal path from Graves’ disease liability to that outcome. A consistent association across instruments would weaken the exclusion restriction, although it would not identify the pleiotropic pathway. Were any instruments selected using prostate cancer associations or outcome-related annotations?

With Graves’ disease liability as the exposure and prostate cancer as the outcome, a negative-control association would challenge the causal interpretation, but would not by itself identify horizontal pleiotropy. Population structure, sample overlap, or outcome-informed instrument selection could produce the same pattern. Were any instruments selected or retained using prostate cancer associations, shared immune annotations, or machine-learning features derived from both traits?