Analysis code for: Triglyceride biology as a non-hormonal metabolic axis in heavy menstrual bleeding: human-genetic and multi-omic drug-target prioritization

This repository contains the analysis code accompanying the manuscript: “Triglyceride biology as a non-hormonal metabolic axis in heavy menstrual bleeding: human-genetic and multi-omic drug-target prioritization” submitted to the *American Journal of Obstetrics and Gynecology*. ## Scope The repository reproduces a prespecified two-sample Mendelian randomization (MR) analysis of 11 systemic exposures against two heavy menstrual bleeding outcomes: FinnGen R12 menorrhagia (28,642 cases) and GWAS Catalog study GCST90483501 (31,309 cases). Drug-target analyses evaluate seven triglyceride-network targets using cis-MR and colocalization. LD-aware generalized inverse-variance weighted analysis of extended-cis, LD-correlated instruments is the primary estimator, with strict-cis LD-unaware sensitivity analyses reported in Supplementary Table S2. The repository also includes safety cis-MR analyses of the prioritized target, apolipoprotein C-III (apoC-III). Endometrial multi-omic analyses integrate bulk and single-cell expression, co-expression networks from GSE199849, statistical fine-mapping, LINCS drug-perturbation signatures, and in silico structural analyses using AutoDock Vina. These analyses characterize tissue localization and candidate mechanisms but do not establish or experimentally validate causal mechanisms. ## Contents The archive includes: - scripts for harmonisation, forward MR, multivariable MR, LD-aware and LD-unaware cis-MR, colocalization, safety cis-MR, multi-omic mapping, structural analyses, and figure generation; - `PROVENANCE_MAP.tsv`, linking scripts to manuscript figures, tables, and supplementary items; - R and Python environment specifications in `R_packages.txt`, `requirements.txt`, and `ENV_VERSIONS.md`; - installation, data-retrieval, and execution instructions in `README.md`; and - `SHA256SUMS.txt`, containing checksums for the archive payload files. ## Data availability Raw GWAS summary statistics are not redistributed. Required datasets are identified by their original accessions or sources, including FinnGen R12, GWAS Catalog GCST accessions, GTEx v8, and the additional datasets listed in Supplementary Table S1. Users should obtain source data directly from the original providers using `GWAS_accessions.txt` and the retrieval instructions in `README.md`. Use and redistribution remain subject to the terms of the respective repositories and consortia. ## Usage Install the specified R and Python environments, retrieve the required source data, and follow `README.md`. After configuring the inputs, run `smoke_test.sh` to perform the packaged integrity and workflow checks. ## Citation Please cite both the accompanying manuscript and this Mendeley Data record. The manuscript DOI will be added after publication.