MR-link-2: pleiotropy robust cis Mendelian randomization validated in three independent reference datasets of causality

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Detalles Bibliográficos
Publicado en:	Nature Communications vol. 16, no. 1 (2025), p. 6112
Autor principal:	van der Graaf, Adriaan
Otros Autores:	Warmerdam, Robert, Auwerx, Chiara, Boltz, Toni, Boomsma, Dorret I., Brown, Andrew, Cheruiyot, Evans, Davenport, Emma E., Dupuis, Théo, Esko, Tõnu, Farzeen, Aiman, Ferrucci, Luigi, Frayling, Timothy M., Gibson, Greg, Gieger, Christian, van Greevenbroek, Marleen, Mishra, Binisha Hamal, Ikram, M. Arfan, Inouye, Michael, Jansen, Rick, Kähönen, Mika, Kukushkina, Viktorija, Lapinska, Sandra, Lehtimäki, Terho, Mägi, Reedik, Martinez-Perez, Angel, McRae, Allan F., van Meurs, Joyce, Milani, Lili, Montgomery, Grant W., Nagpal, Sini, Nauck, Matthias, Ophoff, Roel, Pasaniuc, Bogdan, Paul, Dirk S., Persyn, Elodie, Peters, Annette, Prokisch, Holger, Raitakari, Olli T., Raitoharju, Emma, Singleton, Andrew, Slagboom, Eline, Soria, José Manuel, Souto, Juan Carlos, Teumer, Alexander, Tokolyi, Alex, Veldink, Jan, Verlouw, Joost, Viñuela, Ana, Visscher, Peter M., Völker, Uwe, Weiss, Stefan, Westra, Harm-Jan, Wood, Andrew R., Xie, Manke, Võsa, Urmo, Borges, Maria Carolina, Franke, Lude, Kutalik, Zoltán
Publicado:	Nature Publishing Group
Materias:	Statistics Pleiotropy Pyruvic acid Violations Datasets Quantitative trait loci Genetic variance Phenotypes Causality Metabolites Linkage disequilibrium Gene mapping Genes Blood Citric acid Heterogeneity Simulation Metabolic pathways Gene expression Risk factors Randomization Methods Robustness (mathematics) Tricarboxylic acid cycle Blood cells Meta-analysis Genetic diversity Social
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Descripción
Resumen:	Mendelian randomization (MR) identifies causal relationships from observational data but has increased Type 1 error rates (T1E) when genetic instruments are limited to a single associated region, a typical scenario for molecular exposures. We developed MR-link-2, which leverages summary statistics and linkage disequilibrium (LD) to estimate causal effects and pleiotropy in a single region. We compare MR-link-2 to other cis MR methods: i) In simulations, MR-link-2 has calibrated T1E and high power. ii) We reidentify metabolic reactions from three metabolic pathway references using four independent metabolite quantitative trait locus studies. MR-link-2 often (76%) outperforms other methods in area under the receiver operator characteristic curve (AUC) (up to 0.80). iii) For canonical causal relationships between complex traits, MR-link-2 has lower per-locus T1E (0.096 vs. min. 0.142, at 5% level), identifying all but one of the true causal links, reducing cross-locus causal effect heterogeneity to almost half. iv) Testing causal direction between blood cell compositions and marker gene expression shows MR-link-2 has superior AUC (0.82 vs. 0.68). Finally, analyzing causality between metabolites not directly connected by canonical reactions, only MR-link-2 identifies the causal relationship between pyruvate and citrate (α̂<inline-graphic specific-use="web" mime-subtype="GIF" xlink:href="41467_2025_60868_Article_IEq1.gif" /> = 0.11, P =  7.2⋅10−7), a key citric acid cycle reaction. Overall, MR-link-2 identifies pleiotropy-robust causality from summary statistics in single associated regions, making it well suited for applications to molecular phenotypes.Mendelian randomization (MR) identifies causal relationships from observational data but has increased error rates when the genetic variants used as instruments come from a single region, a typical scenario when assessing molecular traits like protein or metabolite levels as risk factors. Here the authors introduce a single-region pleiotropy-robust MR method, validating the method on three ground truth sources, showing its capability to identify disease-causing molecular traits.
ISSN:	2041-1723
DOI:	10.1038/s41467-025-60868-1
Fuente:	Health & Medical Collection