MR-link-2: pleiotropy robust cis Mendelian randomization validated in three independent reference datasets of causality
Adriaan van der Graaf, Robert Warmerdam, Chiara Auwerx, Toni Boltz, Dorret I. Boomsma, Andrew Brown, Evans Cheruiyot, Emma E. Davenport, Théo Dupuis, Tõnu Esko, Aiman Farzeen, Luigi Ferrucci, Timothy M. Frayling, Greg Gibson, Christian Gieger, Marleen van Greevenbroek, Binisha Hamal Mishra, M. Arfan Ikram, Michael Inouye, Rick Jansen, Mika Kähönen, Viktorija Kukushkina, Sandra Lapinska, Terho Lehtimäki, Reedik Mägi, Angel Martinez-Perez, Allan F. McRae, Joyce van Meurs, Lili Milani, Grant W. Montgomery, Sini Nagpal, Matthias Nauck, Roel Ophoff, Bogdan Pasaniuc, Dirk S. Paul, Elodie Persyn, Annette Peters, Holger Prokisch, Olli T. Raitakari, Emma Raitoharju, Andrew Singleton, Eline Slagboom, José Manuel Soria, Juan Carlos Souto, Alexander Teumer, Alex Tokolyi, Jan Veldink, Joost Verlouw, Ana Viñuela, Peter M. Visscher, Uwe Völker, Stefan Weiss, Harm-Jan Westra, Andrew R. Wood, Manke Xie, Urmo Võsa, Maria Carolina Borges, Lude Franke, Zoltán Kutalik
Abstract
Abstract 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 ( $$\hat{\alpha }$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mover> <mml:mrow> <mml:mi>α</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>̂</mml:mo> </mml:mrow> </mml:mover> </mml:math> = 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.