Results 1 to 10 of about 4,362,965 (333)

Addressing the credibility crisis in Mendelian randomization

BMC Medicine
Background Genome-wide association studies have enabled Mendelian randomization analyses to be performed at an industrial scale. Two-sample summary data Mendelian randomization analyses can be performed using publicly available data by anyone who has ...
Stephen Burgess, Benjamin Woolf, Amy M. Mason, Mika Ala-Korpela, Dipender Gill   +4 more
doaj   +5 more sources

MendelianRandomization v0.9.0: updates to an R package for performing Mendelian randomization analyses using summarized data [version 2; peer review: 2 approved]

Wellcome Open Research, 2023
The MendelianRandomization package is a software package written for the R software environment that implements methods for Mendelian randomization based on summarized data.
Stephen Burgess, Ting Ye, Ashish Patel, Zhaotong Lin, Amy M. Mason, Haoran Xue, Benjamin Woolf, Siqi Xu   +7 more
doaj   +2 more sources

Associations of 35 Serum and Urine Biomarkers With Vascular Dementia—A Mendelian Randomization Study [PDF]

Brain and Behavior
Background The relationship between serum and urine biomarkers with vascular dementia (VD) has been increasingly highlighted by observational studies. Yet, the causal nature underlying these associations remains elusive.
Xiaomin Zhu, Yanan Hu, Jieshuang Lin, Guifeng Zhuo, Yingrui Huang, Yulan Fu, Ying Zhang, Lin Wu, Wei Chen   +8 more
doaj   +2 more sources

Multivariable Mendelian randomization: the use of pleiotropic genetic variants to estimate causal effects. [PDF]

American Journal of Epidemiology, 2015
A conventional Mendelian randomization analysis assesses the causal effect of a risk factor on an outcome by using genetic variants that are solely associated with the risk factor of interest as instrumental variables. However, in some cases, such as the
Burgess, Stephen, Thompson, Simon G
core   +6 more sources

Strengthening the Reporting of Observational Studies in Epidemiology Using Mendelian Randomization: The STROBE-MR Statement.

Journal of the American Medical Association (JAMA), 2021
Importance Mendelian randomization (MR) studies use genetic variation associated with modifiable exposures to assess their possible causal relationship with outcomes and aim to reduce potential bias from confounding and reverse causation.
V. Skrivankova, R. Richmond, B. Woolf, J. Yarmolinsky, N. Davies, S. Swanson, T. VanderWeele, J. Higgins, N. Timpson, N. Dimou, C. Langenberg, Robert M. Golub, E. Loder, V. Gallo, A. Tybjaerg-hansen, G. Davey Smith, M. Egger, J. B. Richards   +17 more
semanticscholar   +1 more source

COVID-19 is associated with the risk of cardiovascular disease death: A two-sample Mendelian randomization study

Frontiers in Cardiovascular Medicine, 2022
ObjectiveThis study aimed to estimate the causal effects of Coronavirus disease 2019 susceptibility and hospitalization on cardiovascular disease death using two-sample Mendelian randomization analysis.MethodsWe used statistics from a genome-wide ...
Jia-peng Miao, Xiao-yu Gu, Rui-zheng Shi
doaj   +1 more source

MendelianRandomization v0.5.0: updates to an R package for performing Mendelian randomization analyses using summarized data [version 2; peer review: 1 approved, 2 approved with reservations]

Wellcome Open Research, 2020
The MendelianRandomization package is a software package written for the R software environment that implements methods for Mendelian randomization based on summarized data. In this manuscript, we describe functions that have been added to the package or
Jim R. Broadbent, Christopher N. Foley, Andrew J. Grant, Amy M. Mason, James R. Staley, Stephen Burgess   +5 more
doaj   +1 more source

Causal relationship between obesity and iron deficiency anemia: a two-sample Mendelian randomization study

Frontiers in Public Health, 2023
BackgroundObservational studies have suggested an association between obesity and iron deficiency anemia, but such studies are susceptible to reverse causation and residual confounding.
Tingting Wang, Qi Gao, Yuanyuan Yao, Ge Luo, Tao Lv, Guangxin Xu, Mingxia Liu, Jingpin Xu, Xuejie Li, Dawei Sun, Zhenzhen Cheng, Ying Wang, Chaomin Wu, Ruiyu Wang, Jingcheng Zou, Min Yan   +15 more
doaj   +1 more source

Genome-wide and Mendelian randomisation studies of liver MRI yield insights into the pathogenesis of steatohepatitis [PDF]

, 2020
Background A non-invasive method to grade the severity of steatohepatitis and liver fibrosis is magnetic resonance imaging (MRI) based corrected T1 (cT1).
Banerjee, R, Banerjee, R, Bell, J.D., Bell, J.D., Hemingway, H., Hemingway, H., Hingorani, A.D., Hingorani, A.D., Kelly, M., Kelly, M., McGonigle, J., McGonigle, J., Neubauer, S., Neubauer, S., Nicholls, R.C., Nicholls, R.C., Parisinos, C.A., Parisinos, C.A., Patel, R.S., Patel, R.S., Thomas, E.L., Thomas, E.L., Wilman, H., Wilman, H., Yaghootkar, H., Yaghootkar, H.   +25 more
core   +3 more sources

MendelianRandomization v0.9.0: updates to an R package for performing Mendelian randomization analyses using summarized data [version 1; peer review: 2 approved]

Wellcome Open Research, 2023
The MendelianRandomization package is a software package written for the R software environment that implements methods for Mendelian randomization based on summarized data.
Stephen Burgess, Ting Ye, Ashish Patel, Zhaotong Lin, Amy M. Mason, Haoran Xue, Benjamin Woolf, Siqi Xu   +7 more
doaj   +1 more source