scholarly journals Welch-weighted Egger regression reduces false positives due to correlated pleiotropy in Mendelian randomization

2021 ◽  
Vol 108 (12) ◽  
pp. 2319-2335
Author(s):  
Brielin C. Brown ◽  
David A. Knowles
Keyword(s):  
Mendelian Randomization ◽  
False Positives

scholarly journals Mendelian randomization accounting for correlated and uncorrelated pleiotropic effects using genome-wide summary statistics

2019 ◽  
Author(s):  
Jean Morrison ◽  
Nicholas Knoblauch ◽  
Joseph Marcus ◽  
Matthew Stephens ◽  
Xin He
Keyword(s):  
Genetic Variant ◽  
Mendelian Randomization ◽  
Association Studies ◽  
False Positives ◽  
Pleiotropic Effects ◽  
Alternative Methods ◽  
Genome Wide Association Studies ◽  
Causal Relationships ◽  
Genome Wide ◽  
Summary Effect

AbstractMendelian randomization (MR) is a valuable tool for detecting evidence of causal relationships using genetic variant associations. Opportunities to apply MR are growing rapidly with the number of genome-wide association studies (GWAS) with publicly available results. However, existing MR methods rely on strong assumptions that are often violated, leading to false positives. Many methods have been proposed loosening these assumptions. However, it has remained challenging to account for correlated pleiotropy, which arises when variants affect both traits through a heritable shared factor. We propose a new MR method, Causal Analysis Using Summary Effect Estimates (CAUSE), that accounts for correlated and uncorrelated horizontal pleiotropic effects. We demonstrate in simulations that CAUSE is more robust to correlated pleiotropy than other methods. Applied to traits studied in recent GWAS, we find that CAUSE detects causal relationships with strong literature support and avoids identifying most unlikely relationships. Our results suggest that many pairs of traits identified as causal using alternative methods may be false positives due to horizontal pleiotropy.

scholarly journals Welch-weighted Egger regression reduces false positives due to correlated pleiotropy in Mendelian randomization

2021 ◽  
Author(s):  
Brielin C Brown ◽  
David A Knowles
Keyword(s):  
Exploratory Data Analysis ◽  
Mendelian Randomization ◽  
False Positives ◽  
Causal Effects ◽  
Genetic Associations ◽  
Exploratory Data ◽  
Flexible Framework ◽  
The Uk ◽  
Modern Population ◽  
The Relationship

Modern population-scale biobanks contain simultaneous measurements of many phenotypes, providing unprecedented opportunity to study the relationship between biomarkers and disease. However, inferring causal effects from observational data is notoriously challenging. Mendelian randomization (MR) has recently received increased attention as a class of methods for estimating causal effects using genetic associations. However, standard methods result in pervasive false positives when two traits share a heritable, unobserved common cause. This is the problem of correlated pleiotropy. Here, we introduce a flexible framework for simulating traits with a common genetic confounder that generalizes recently proposed models, as well as simple approach we call Welch-weighted Egger regression (WWER) for estimating causal effects. We show in comprehensive simulations that our method substantially reduces false positives due to correlated pleiotropy while being fast enough to apply to hundreds of phenotypes. We first apply our method to a subset of the UK Biobank consisting of blood traits in inflammatorydisease, and then a broader set of 411 heritable phenotypes. We detect many effects with strong literaturesupport, as well as numerous behavioral effects that appear to stem from physician advice given to peopleat high risk for disease. We conclude that WWER is a powerful tool for exploratory data analysis inever-growing databases of genotypes and phenotypes

False Positives on the PTSD Checklist (PCL) Among Outpatients With Substance Abuse Disorders (SUD)

2008 ◽  
Author(s):  
Judith Andersen ◽  
Rebecca Silver ◽  
Todd Bishop ◽  
Vanessa Tirone ◽  
Paige Ouimette
Keyword(s):  
Substance Abuse ◽  
False Positives ◽  
Ptsd Checklist ◽  
Substance Abuse Disorders

False Positives Prevalent in Some Cancer Screenings

2007 ◽  
Vol 37 (15) ◽  
pp. 38
Author(s):  
SARAH PRESSMAN LOVINGER
Keyword(s):  
False Positives ◽  
Cancer Screenings

257-OR: High Glucose Levels and Risk of Vascular Diseases—Observational Studies and Mendelian Randomization Studies of the General Population

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 257-OR
Author(s):  
FRIDA EMANUELSSON ◽  
SARAH MAROTT ◽  
ANNE TYBJAERG-HANSEN ◽  
BØRGE GRØNNE NORDESTGAARD ◽  
MARIANNE BENN
Keyword(s):  
General Population ◽  
High Glucose ◽  
Observational Studies ◽  
Mendelian Randomization ◽  
Vascular Diseases ◽  
Glucose Levels
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