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He/Him/His
Job Title
Postdoc
Academic Rank
Fellow or Postdoc
Department
Medicine
Authors
Lovemore Kunorozva, Michael Weedon, Andrew Wood, Matthew Maher, Richa Saxena, Samuel Jones, Hanna M Ollila, Jacqueline M Lane
Principal Investigator
Lovemore Kunorozva
Categories
Tags
Background: Sleep is a ubiquitous, complex neurological and psychological state that is essential for well-being, performance, and health and any perturbation to sleep may lead to sleep/circadian disorders. While genetic research has been conducted on sleep/circadian traits, a comprehensive interrogation of the genetic associations with both clinically diagnosed disorders and medication treatment has not been performed.
Aim: This study aims to identify common variants associated with sleep/circadian related ICD10-codes and medications used to treat sleep-related disorders.
Methods: We pooled data from GWAS conducted in the UK Biobank, MassGeneralBrigham and FinnGen cohorts. We performed a meta-analysis on 765,831 controls and 127,622 cases with various sleep/circadian disorders and medications used to treat sleep/circadian disorders. Genome-wide significant hits in each META-analysis (p < 5×10-8) were identified.
Results: The association of FTO (chr16: 53,769,311) with sleep apnea, MEIS1 (chr2: 66,523,432) with restless-leg syndrome, and HLA (chr6: 33,392,686) with narcolepsy confirms previously reported loci. Genetic variants in MEIS1 (chr2: 66,523,432), BTN2A2 (chr6: 26,392,287) and ZNF197 (chr3: 44,610,795) were associated with zopiclone, oxazepam and zolpidem, respectively.
Conclusion and Discussion: Identification of common variants may increase our ability to assess risk for sleep/circadian disorders before symptom onset, allowing us to shift focus from treatment to prevention.
Background: Sleep is a ubiquitous, complex neurological and psychological state that is essential for well-being, performance, and health and any perturbation to sleep may lead to sleep/circadian disorders. While genetic research has been conducted on sleep/circadian traits, a comprehensive interrogation of the genetic associations with both clinically diagnosed disorders and medication treatment has not been performed.
Aim: This study aims to identify common variants associated with sleep/circadian related ICD10-codes and medications used to treat sleep-related disorders.
Methods: We pooled data from GWAS conducted in the UK Biobank, MassGeneralBrigham and FinnGen cohorts. We performed a meta-analysis on 765,831 controls and 127,622 cases with various sleep/circadian disorders and medications used to treat sleep/circadian disorders. Genome-wide significant hits in each META-analysis (p < 5×10-8) were identified.
Results: One hundred and twenty-two significant genome-wide loci were identified in six sleep related disorders, including sleep apnea (n=60), restless leg syndrome (n=12) and narcolepsy (n=5). Likewise, one hundred and seventy-five significant genome-wide loci were identified for ten insomnia medications.
Conclusion and Discussion: Identification of common variants may increase our ability to assess risk for sleep/circadian disorders before symptom onset, allowing us to shift focus from treatment to prevention.
