Causal inference for multiple risk factors and diseases from genomics data

Abstract excerpt

Abstract Statistical causal learning in genome-wide association studies (GWAS) relies on the instrumental variable method of Mendelian Randomization (MR). Currently, an over-whelming number of MR studies purport to show causal relationships among a wide range of risk factors and outcomes. Here, we find that naive application of many recently proposed MR approaches results in numerous null relationships being disco...

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• Bioinformatics and Genomic Networks
• Genetic Associations and Epidemiology
• Lipoproteins and Cardiovascular Health

Identifiers and source

Literature Corpus work

1488b59e-cb67-57df-a8d0-f5ad32b667bf

DOI

10.1038/s41467-026-76877-7