Evidence map›Paper›PMID 35897932›Full record

ArticleMolecules (Basel, Switzerland)2022

Lipoprotein Subclasses Independently Contribute to Subclinical Variance of Microvascular and Macrovascular Health.

Lukas Streese, Hansjörg Habisch, Arne Deiseroth, Justin Carrard, Denis Infanger, Arno Schmidt-Trucksäss, Tobias Madl, Henner Hanssen

Abstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

7 citing papers in PubMed.

  1. Trial
  2. Article
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  6. Review
  7. Review
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.

Lukas StreeseDepartment of Sport, Exercise and Health, Medical Faculty, University of Basel, 4052 Basel, Switzerland.ORCID 0000-0003-3920-8610
Hansjörg HabischGottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, 8010 Graz, Austria.ORCID 0000-0001-5537-506X
Arne DeiserothDepartment of Sport, Exercise and Health, Medical Faculty, University of Basel, 4052 Basel, Switzerland.
Justin CarrardDepartment of Sport, Exercise and Health, Medical Faculty, University of Basel, 4052 Basel, Switzerland.ORCID 0000-0002-2380-105X
Denis InfangerDepartment of Sport, Exercise and Health, Medical Faculty, University of Basel, 4052 Basel, Switzerland.
Arno Schmidt-TrucksässDepartment of Sport, Exercise and Health, Medical Faculty, University of Basel, 4052 Basel, Switzerland.
Tobias MadlGottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, 8010 Graz, Austria.ORCID 0000-0002-9725-5231
Henner HanssenDepartment of Sport, Exercise and Health, Medical Faculty, University of Basel, 4052 Basel, Switzerland.

Funding

Austrian Research Promotion Agency 864690Austrian Research Promotion Agency 870454Austrian Science Fund FWF I 3792Austrian Science Fund FWF W 1226FWF Austrian Science Fund DK-MCD W1226FWF Austrian Science Fund DOC-130FWF Austrian Science Fund I3792FWF Austrian Science Fund P28854Swiss National Science Foundation 32003B_159518/1
6 · The paper itself

Abstract

Lipoproteins are important cardiovascular (CV) risk biomarkers. This study aimed to investigate the associations of lipoprotein subclasses with micro- and macrovascular biomarkers to better understand how these subclasses relate to atherosclerotic CV diseases. One hundred and fifty-eight serum samples from the EXAMIN AGE study, consisting of healthy individuals and CV risk patients, were analysed with nuclear magnetic resonance (NMR) spectroscopy to quantify lipoprotein subclasses. Microvascular health was quantified by measuring retinal arteriolar and venular diameters. Macrovascular health was quantified by measuring carotid-to-femoral pulse wave velocity (PWV). Nineteen lipoprotein subclasses showed statistically significant associations with retinal vessel diameters and nine with PWV. These lipoprotein subclasses together explained up to 26% of variation (R2 = 0.26, F(29,121) = 2.80, p < 0.001) in micro- and 12% (R2 = 0.12, F(29,124) = 1.70, p = 0.025) of variation in macrovascular health. High-density (HDL-C) and low-density lipoprotein cholesterol (LDL-C) as well as triglycerides together explained up to 13% (R2 = 0.13, F(3143) = 8.42, p < 0.001) of micro- and 8% (R2 = 0.08, F(3145) = 5.46, p = 0.001) of macrovascular variation. Lipoprotein subclasses seem to reflect micro- and macrovascular end organ damage more precisely as compared to only measuring HDL-C, LDL-C and triglycerides. Further studies are needed to analyse how the additional quantification of lipoprotein subclasses can improve CV risk stratification and CV disease prediction.

Indexed as

LipoproteinsPulse Wave AnalysisBiomarkersCholesterol, LDLHumansLipoproteins, LDLTriglyceridesBiomarkersCholesterol, LDLLipoproteinsLipoproteins, LDLTriglyceridescardiovascular risklipidsNMR spectroscopypulse wave velocityretinal vessel diameters

Identifiers

PMID35897932
PMCPMC9332701

What Socratic holds

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LicenceCC BY
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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 Socratic graph.