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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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What is an Experiment?01:12

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An experiment is a planned activity carried out under controlled conditions. The purpose of an experiment is to investigate the relationship between two variables. When one variable causes change in another, we call the first variable the explanatory or independent variable. The affected variable is called the response or dependent variable. In a randomized experiment, the researcher manipulates values of the explanatory variable and measures the resulting changes in the response variable. The...
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Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
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Mendelian randomization with proxy exposures: challenges and opportunities.

Ida Rahu1,2, Ralf Tambets1, Eric B Fauman3

  • 1Institute of Computer Science, University of Tartu, Tartu 51009, Estonia.

Genetics
|September 26, 2025
PubMed
Summary
This summary is machine-generated.

Mendelian randomization (MR) can identify causal risk factors for diseases. This study introduces a cis-MR framework using metabolite levels as proxy exposures to overcome challenges like horizontal pleiotropy, successfully identifying causal links in vitamin D synthesis and red blood cell survival.

Keywords:
HALMendelian randomizationUK Biobankglycolysispleiotropyvitamin D

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Area of Science:

  • Human genetics
  • Complex trait analysis
  • Biomarker discovery

Background:

  • Identifying modifiable causal risk factors for complex diseases is crucial in human genetics.
  • Mendelian randomization (MR) is a powerful tool for this, but horizontal pleiotropy presents a significant challenge.
  • Previous MR studies on biomarkers like cholesterol and C-reactive protein have shown promise but also revealed complexities.

Purpose of the Study:

  • To address the challenge of horizontal pleiotropy in Mendelian randomization.
  • To illustrate how cis-MR with proxy exposures can overcome pleiotropy.
  • To rediscover causal relationships in vitamin D synthesis and glycolysis using metabolite levels.

Main Methods:

  • Utilized UK Biobank data for two case studies: glycolysis and vitamin D synthesis.
  • Employed a cis-MR framework with metabolite levels (pyruvate, histidine) as proxy exposures.
  • Analyzed variant effects on downstream metabolites to infer protein function perturbations.

Main Results:

  • Demonstrated that measured metabolites (pyruvate, histidine) did not directly cause outcomes (red blood cell count, vitamin D level).
  • Successfully used variant effects on metabolite levels as proxy exposures in cis-MR.
  • Rediscovered the causal roles of histidine ammonia lyase (HAL) in vitamin D synthesis and glycolysis in red blood cell survival.

Conclusions:

  • Cis-MR with proxy exposures can overcome horizontal pleiotropy in Mendelian randomization.
  • This approach allows for the inference of causal relationships even when direct metabolite effects are absent.
  • Highlights the assumptions and practical challenges for valid cis-MR inferences with proxy exposures.