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Related Concept Videos

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The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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Related Experiment Video

Updated: Dec 19, 2025

Transposon Mediated Integration of Plasmid DNA into the Subventricular Zone of Neonatal Mice to Generate Novel Models of Glioblastoma
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Testing for causality between systematically identified risk factors and glioma: a Mendelian randomization study.

A E Howell1, J W Robinson1, R E Wootton2,3,4

  • 1Brain Tumour Research Centre, Institute of Clinical Neurosciences, University of Bristol, Bristol, UK.

BMC Cancer
|June 5, 2020
PubMed
Summary

Mendelian randomization identified four traits causally linked to increased glioma risk: longer leukocyte telomere length, allergy, alcohol consumption, and extreme childhood obesity. Two traits, LDL cholesterol and triglycerides, reduced non-glioblastoma risk.

Keywords:
Causal inferenceGliomaMendelian randomizationRisk factorSystematic search

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Area of Science:

  • Genetics and Epidemiology
  • Cancer Research
  • Causal Inference

Background:

  • Epidemiological studies suggest associations between risk factors and glioma, but establishing causality is difficult.
  • Mendelian randomization (MR) is a powerful tool for inferring causality from observational data.
  • This study investigates 36 reported glioma risk factors for causal relationships using MR.

Purpose of the Study:

  • To determine the causal effect of 36 reported risk factors on glioma onset using Mendelian randomization.
  • To explore potential differences in risk factors between glioblastoma and non-glioblastoma subtypes.

Main Methods:

  • Systematic literature search for candidate risk factors and meta-analysis of glioma genome-wide association studies.
  • Utilized genetic variants as instrumental variables for risk factors in MR analyses.
  • Employed inverse-variance weighting (IVW) and sensitivity analyses (MR-Egger, weighted median, mode-based) to assess pleiotropy.

Main Results:

  • Identified four genetically predicted traits causally associated with increased glioma risk: longer leukocyte telomere length, liability to allergic disease, increased alcohol consumption, and liability to childhood extreme obesity.
  • Found that increased low-density lipoprotein cholesterol (LDLc) and triglyceride levels were causally associated with decreased risk of non-glioblastoma.
  • Results remained consistent across sensitivity analyses accounting for pleiotropy.

Conclusions:

  • Provides evidence for a causal link between genetically predicted leukocyte telomere length, allergic disease, alcohol consumption, childhood extreme obesity, LDLc, and triglyceride levels with glioma.
  • Highlights the need for further research into the underlying mechanisms connecting these traits to glioma development.