Evidence map›Paper›PMID 35289444›Full record

Observational studyJournal of internal medicine2022

Genetic and observational evidence: No independent role for cholesterol efflux over static high-density lipoprotein concentration measures in coronary heart disease risk assessment.

Sanna Kuusisto, Minna K Karjalainen, Therese Tillin, Antti J Kangas, Michael V Holmes, Mika Kähönen, Terho Lehtimäki, Jorma Viikari, Markus Perola, Nishi Chaturvedi and 5 more

Open access · hybridAbstract readObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in Journal of internal medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.1field-weighted citation impact, top 21% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Article
  3. Observational
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

15 authors at 11 institutions in 4 countries.

Sanna KuusistoComputational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland.
Minna K KarjalainenComputational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland.
Therese TillinMRC Unit for Lifelong Health and Ageing at UCL, Institute of Cardiovascular Science, University College London, London, UK.
Antti J KangasNightingale Health Plc., Helsinki, Finland.
Michael V HolmesMedical Research Council Population Health Research Unit, University of Oxford, Oxford, UK.
Mika KähönenDepartment of Clinical Physiology, Tampere University Hospital and Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
Terho LehtimäkiDepartment of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
Jorma ViikariDepartment of Medicine, University of Turku, Turku, Finland.
Markus PerolaResearch Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland.
Nishi ChaturvediMRC Unit for Lifelong Health and Ageing at UCL, Institute of Cardiovascular Science, University College London, London, UK.
Veikko SalomaaDepartment of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland.
Olli T RaitakariCentre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland.
Marjo-Riitta JärvelinCenter for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland.
Johannes KettunenComputational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland.
Mika Ala-KorpelaComputational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland.ORCID 0000-0001-5905-1206
Finnish Institute for Health and Welfare · FIMRC Unit for Lifelong Health and Ageing · GBUniversity of Eastern Finland · FIUniversity of Turku · FINightingales Medical Trust · INOulu University Hospital · FIOulu University of Applied Sciences · FITampere University Hospital · FITampere University of Applied Sciences · FIUniversity of Helsinki · FIUniversity of Oxford · GB

Funding

British Heart Foundation CS/13/1/30327Medical Research Council MR/S019669/1
6 · The paper itself

Abstract

backgroundObservational findings for high-density lipoprotein (HDL)-mediated cholesterol efflux capacity (HDL-CEC) and coronary heart disease (CHD) appear inconsistent, and knowledge of the genetic architecture of HDL-CEC is limited.

objectivesA large-scale observational study on the associations of HDL-CEC and other HDL-related measures with CHD and the largest genome-wide association study (GWAS) of HDL-CEC. PARTICIPANTS/

methodsSix independent cohorts were included with follow-up data for 14,438 participants to investigate the associations of HDL-related measures with incident CHD (1,570 events). The GWAS of HDL-CEC was carried out in 20,372 participants.

resultsHDL-CEC did not associate with CHD when adjusted for traditional risk factors and HDL cholesterol (HDL-C). In contradiction, almost all HDL-related concentration measures associated consistently with CHD after corresponding adjustments. There were no genetic loci associated with HDL-CEC independent of HDL-C and triglycerides.

conclusionHDL-CEC is not unequivocally associated with CHD in contrast to HDL-C, apolipoprotein A-I, and most of the HDL subclass particle concentrations.

Indexed as

Coronary DiseaseLipoproteins, HDLCholesterol, HDLGenome-Wide Association StudyHumansRisk AssessmentRisk FactorsCholesterol, HDLLipoproteins, HDLcholesterol effluxcoronary heart diseasegenome-wide association studyHDLobservational cohort studytriglycerides

Identifiers

PMID35289444
PMCPMC9311699
OpenAlexW4221007974

What OpenQuestion holds

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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.