@article{vanKippersluis2017,
title = {Pleiotropy-robust Mendelian randomization},
author = { Hans van Kippersluis, Cornelius A. Rietveld},
url = {https://academic.oup.com/ije/article-abstract/doi/10.1093/ije/dyx002/3039345/Pleiotropy-robust-Mendelian-randomization?redirectedFrom=fulltext},
year = {2017},
date = {2017-02-22},
journal = {International Journal of Epidemiology},
abstract = {Background: The potential of Mendelian randomization studies is rapidly expanding due to: (i) the growing power of genome-wide association study (GWAS) meta-analyses to detect genetic variants associated with several exposures; and (ii) the increasing availability of these genetic variants in large-scale surveys. However, without a proper biological understanding of the pleiotropic working of genetic variants, a fundamental assumption of Mendelian randomization (the exclusion restriction) can always be contested.

Methods: We build upon and synthesize recent advances in the literature on instrumental variables (IVs) estimation that test and relax the exclusion restriction. Our pleiotropy-robust Mendelian randomization (PRMR) method first estimates the degree of pleiotropy, and in turn corrects for it. If (i) a subsample exists for which the genetic variants do not affect the exposure; (ii) the selection into this subsample is not a joint consequence of the IV and the outcome; (iii) pleiotropic effects are homogeneous, PRMR obtains unbiased estimates of causal effects.

Results: Simulations show that existing MR methods produce biased estimators for realistic forms of pleiotropy. Under the aforementioned assumptions, PRMR produces unbiased estimators. We illustrate the practical use of PRMR by estimating the causal effect of: (i) tobacco exposure on body mass index (BMI); (ii) prostate cancer on self-reported health; and (iii) educational attainment on BMI in the UK Biobank data.

Conclusions: PRMR allows for instrumental variables that violate the exclusion restriction due to pleiotropy, and it corrects for pleiotropy in the estimation of the causal effect. If the degree of pleiotropy is unknown, PRMR can still be used as a sensitivity analysis.},
keywords = {11425, Medelian randomization, pleiotropy},
pubstate = {published},
tppubtype = {article}
}

@article{Okbay2016,
title = {Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses.},
author = {Okbay A, Baselmans BM, De Neve JE, Turley P, Nivard MG, Fontana MA, Meddens SF, Linnér RK, Rietveld CA, Derringer J, Gratten J, Lee JJ, Liu JZ, de Vlaming R, Ahluwalia TS, Buchwald J, Cavadino A, Frazier-Wood AC, Furlotte NA, Garfield V, Geisel MH, Gonzalez JR, Haitjema S, Karlsson R, van der Laan SW, Ladwig KH, Lahti J, van der Lee SJ, Lind PA, Liu T, Matteson L, Mihailov E, Miller MB, Minica CC, Nolte IM, Mook-Kanamori D, van der Most PJ, Oldmeadow C, Qian Y, Raitakari O, Rawal R, Realo A, Rueedi R, Schmidt B, Smith AV, Stergiakouli E, Tanaka T, Taylor K, Wedenoja J, Wellmann J, Westra HJ, Willems SM, Zhao W; LifeLines Cohort Study, Amin N, Bakshi A, Boyle PA, Cherney S, Cox SR, Davies G, Davis OS, Ding J, Direk N, Eibich P, Emeny RT, Fatemifar G, Faul JD, Ferrucci L, Forstner A, Gieger C, Gupta R, Harris TB, Harris JM, Holliday EG, Hottenga JJ, De Jager PL, Kaakinen MA, Kajantie E, Karhunen V, Kolcic I, Kumari M, Launer LJ, Franke L, Li-Gao R, Koini M, Loukola A, Marques-Vidal P, Montgomery GW, Mosing MA, Paternoster L, Pattie A, Petrovic KE, Pulkki-Råback L, Quaye L, Räikkönen K, Rudan I, Scott RJ, Smith JA, Sutin AR, Trzaskowski M, Vinkhuyzen AE, Yu L, Zabaneh D, Attia JR, Bennett DA, Berger K, Bertram L, Boomsma DI, Snieder H, Chang SC, Cucca F, Deary IJ, van Duijn CM, Eriksson JG, Bültmann U, de Geus EJ, Groenen PJ, Gudnason V, Hansen T, Hartman CA, Haworth CM, Hayward C, Heath AC, Hinds DA, Hyppönen E, Iacono WG, Järvelin MR, Jöckel KH, Kaprio J, Kardia SL, Keltikangas-Järvinen L, Kraft P, Kubzansky LD, Lehtimäki T, Magnusson PK, Martin NG, McGue M, Metspalu A, Mills M, de Mutsert R, Oldehinkel AJ, Pasterkamp G, Pedersen NL, Plomin R, Polasek O, Power C, Rich SS, Rosendaal FR, den Ruijter HM, Schlessinger D, Schmidt H, Svento R, Schmidt R, Alizadeh BZ, Sørensen TI, Spector TD, Steptoe A, Terracciano A, Thurik AR, Timpson NJ, Tiemeier H, Uitterlinden AG, Vollenweider P, Wagner GG, Weir DR, Yang J, Conley DC, Smith GD, Hofman A, Johannesson M, Laibson DI, Medland SE, Meyer MN, Pickrell JK, Esko T, Krueger RF, Beauchamp JP, Koellinger PD, Benjamin DJ, Bartels M, Cesarini D },
url = {http://www.ncbi.nlm.nih.gov/pubmed/?term=Genetic+variants+associated+with+subjective+well-being%2C+depressive+symptoms%2C+and+neuroticism+identified+through+genome-wide+analyses},
year = {2016},
date = {2016-04-18},
journal = {Nature Genetics},
abstract = {Very few genetic variants have been associated with depression and neuroticism, likely because of limitations on sample size in previous studies. Subjective well-being, a phenotype that is genetically correlated with both of these traits, has not yet been studied with genome-wide data. We conducted genome-wide association studies of three phenotypes: subjective well-being (n = 298,420), depressive symptoms (n = 161,460), and neuroticism (n = 170,911). We identify 3 variants associated with subjective well-being, 2 variants associated with depressive symptoms, and 11 variants associated with neuroticism, including 2 inversion polymorphisms. The two loci associated with depressive symptoms replicate in an independent depression sample. Joint analyses that exploit the high genetic correlations between the phenotypes (|ρ^| ≈ 0.8) strengthen the overall credibility of the findings and allow us to identify additional variants. Across our phenotypes, loci regulating expression in central nervous system and adrenal or pancreas tissues are strongly enriched for association.},
keywords = {11425, depression, genetics, neuroticism},
pubstate = {published},
tppubtype = {article}
}