Mendelian Randomization Applied to Neurology.
Eloi GagnonIyas DaghlasLoukas ZagkosMuralidharan SargurupremrajMarios K GeorgakisChristopher D AndersonHelene T CronjeStephen BurgessBenoit J ArsenaultDipender GillPublished in: Neurology (2024)
The Mendelian randomization (MR) paradigm allows for causal inferences to be drawn using genetic data. In recent years, the expansion of well-powered publicly available genetic association data related to phenotypes such as brain tissue gene expression, brain imaging, and neurologic diseases offers exciting opportunities for the application of MR in the field of neurology. In this review, we discuss the basic principles of MR, its myriad applications to research in neurology, and potential pitfalls of injudicious applications. Throughout, we provide examples where MR-informed findings have shed light on long-standing epidemiologic controversies, provided insights into the pathophysiology of neurologic conditions, prioritized drug targets, and informed drug repurposing opportunities. With the ever-expanding availability of genome-wide association data, we project MR to become a key driver of progress in the field of neurology. It is therefore paramount that academics and clinicians within the field are familiar with the approach.
Keyphrases
- contrast enhanced
- gene expression
- magnetic resonance
- electronic health record
- genome wide association
- big data
- magnetic resonance imaging
- genome wide
- white matter
- dna methylation
- high resolution
- palliative care
- emergency department
- copy number
- cerebral ischemia
- computed tomography
- artificial intelligence
- photodynamic therapy
- deep learning
- subarachnoid hemorrhage