Associations of Circulating Biomarkers with Disease Risks: A Two-Sample Mendelian Randomization Study
Abdulkadir Elmas, Kevin Spehar, Ron Do, Joseph M. Castellano, Kuan-Lin Huang

TL;DR
This study uses genetic data to find causal links between 212 biomarkers and 99 diseases, identifying new connections and confirming known ones.
Contribution
The study uncovers two novel causal relationships between biomarkers and bipolar disorder using multiple MR methods.
Findings
Glucose and cystatin C show novel causal links to bipolar disorder.
Urate and creatine confirm known associations with gout and chronic kidney disease.
Lipoprotein A, LDL, cholesterol, and apolipoprotein B are linked to cardiovascular conditions.
Abstract
Circulating biomarkers play a pivotal role in personalized medicine, offering potential for disease screening, prevention, and treatment. Despite established associations between numerous biomarkers and diseases, elucidating their causal relationships is challenging. Mendelian Randomization (MR) can address this issue by employing genetic instruments to discern causal links. Additionally, using multiple MR methods with overlapping results enhances the reliability of discovered relationships. Here, we report an MR study using multiple methods, including inverse variance weighted, simple mode, weighted mode, weighted median, and MR-Egger. We use the MR-base resource (v0.5.6) from Hemani et al. 2018 to evaluate causal relationships between 212 circulating biomarkers (curated from UK Biobank analyses by Neale lab and from Shin et al. 2014, Roederer et al. 2015, and Kettunen et al. 2016 and…
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Taxonomy
TopicsGenetic Associations and Epidemiology · Genetic Syndromes and Imprinting · Liver Disease Diagnosis and Treatment
