Disease areas:
  • brain
  • mental health
Last updated:
Author(s):
Martin Broberg, Viola Helaakoski, Tuomo Kiiskinen, Tiina Paunio, Samuel E Jones, Nina Mars, Jacqueline M Lane, FinnGen, Richa Saxena, Hanna M Ollila
Publish date:
20 November 2023
Journal:
Sleep
PubMed ID:
37982563

Abstract

STUDY OBJECTIVES: Over 10% of the population in Europe and in the United States use sleep medication to manage sleep problems. Our objective was to elucidate genetic risk factors and clinical correlates that contribute to sleep medication purchase and estimate the comorbid impact of sleep problems.

METHODS: We performed epidemiological analysis for psychiatric diagnoses, and genetic association studies of sleep medication purchase in 797 714 individuals from FinnGen Release 7 (N = 311 892) and from the UK Biobank (N = 485 822). Post-association analyses included genetic correlation, co-localization, Mendelian randomization (MR), and polygenic risk estimation.

RESULTS: In a GWAS we identified 27 genetic loci significantly associated with sleep medication, located in genes associated with sleep; AUTS2, CACNA1C, MEIS1, KIRREL3, PAX8, GABRA2, psychiatric traits; CACNA1C, HIST1H2BD, NUDT12. TOPAZ1 and TSNARE1. Co-localization and expression analysis emphasized effects on the KPNA2, GABRA2, and CACNA1C expression in the brain. Sleep medications use was epidemiologically related to psychiatric traits in FinnGen (OR [95% (CI)] = 3.86 [3.78 to 3.94], p < 2 × 10-16), and the association was accentuated by genetic correlation and MR; depression (rg = 0.55 (0.027), p = 2.86 × 10-89, p MR = 4.5 × 10-5), schizophrenia (rg = 0.25 (0.026), p = 2.52 × 10-21, p MR = 2 × 10-4), and anxiety (rg = 0.44 (0.047), p = 2.88 × 10-27, p MR = 8.6 × 10-12).

CONCLUSIONS: These results demonstrate the genetics behind sleep problems and the association between sleep problems and psychiatric traits. Our results highlight the scientific basis for sleep management in treating the impact of psychiatric diseases.

Related projects

We propose to apply statistical fine-mapping methods to the UK Biobank genotype-phenotype data. We study how our recently published summary-data based fine-mapping method works with…

Institution:
University of Helsinki, Finland

All projects