Evidence map›Paper›PMID 37798698›Full record

ArticleBMC medicine2023

Investigating the causal interplay between sleep traits and risk of acute myocardial infarction: a Mendelian randomization study.

Nikhil Arora, Laxmi Bhatta, Eivind Schjelderup Skarpsno, Håvard Dalen, Bjørn Olav Åsvold, Ben Michael Brumpton, Rebecca Claire Richmond, Linn Beate Strand

Open access · goldAbstract read
In one paragraph

Article in BMC medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
3.1field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 3 countries.

Nikhil AroraK.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway. nikhil.arora@ntnu.no.ORCID http://orcid.org/0000-0001-5767-5410
Laxmi BhattaK.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway.
Eivind Schjelderup SkarpsnoDepartment of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway.
Håvard DalenDepartment of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway.
Bjørn Olav ÅsvoldK.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway.
Ben Michael BrumptonK.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway.
Rebecca Claire RichmondPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Linn Beate StrandDepartment of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway.
Norwegian University of Science and Technology · NOThe University of Queensland · AUUniversity of Bristol · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFew studies have investigated the joint effects of sleep traits on the risk of acute myocardial infarction (AMI). No previous study has used factorial Mendelian randomization (MR) which may reduce confounding, reverse causation, and measurement error. Thus, it is prudent to study joint effects using robust methods to propose sleep-targeted interventions which lower the risk of AMI.

methodsThe causal interplay between combinations of two sleep traits (including insomnia symptoms, sleep duration, or chronotype) on the risk of AMI was investigated using factorial MR. Genetic risk scores for each sleep trait were dichotomized at their median in UK Biobank (UKBB) and the second survey of the Trøndelag Health Study (HUNT2). A combination of two sleep traits constituting 4 groups were analyzed to estimate the risk of AMI in each group using a 2×2 factorial MR design.

resultsIn UKBB, participants with high genetic risk for both insomnia symptoms and short sleep had the highest risk of AMI (hazard ratio (HR) 1.10; 95% confidence interval (CI) 1.03, 1.18), although there was no evidence of interaction (relative excess risk due to interaction (RERI) 0.03; 95% CI -0.07, 0.12). These estimates were less precise in HUNT2 (HR 1.02; 95% CI 0.93, 1.13), possibly due to weak instruments and/or small sample size. Participants with high genetic risk for both a morning chronotype and insomnia symptoms (HR 1.09; 95% CI 1.03, 1.17) and a morning chronotype and short sleep (HR 1.11; 95% CI 1.04, 1.19) had the highest risk of AMI in UKBB, although there was no evidence of interaction (RERI 0.03; 95% CI -0.06, 0.12; and RERI 0.05; 95% CI -0.05, 0.14, respectively). Chronotype was not available in HUNT2.

conclusionsThis study reveals no interaction effects between sleep traits on the risk of AMI, but all combinations of sleep traits increased the risk of AMI except those with long sleep. This indicates that the main effects of sleep traits on AMI are likely to be independent of each other.

Indexed as

Myocardial InfarctionSleep Initiation and Maintenance DisordersGenome-Wide Association StudyHumansMendelian Randomization AnalysisRisk FactorsSleepChronotypeInsomniaMendelian randomizationMyocardial infarctionSleep duration

Identifiers

PMID37798698
PMCPMC10557341
OpenAlexW4387359246

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.