Evidence map›Paper›PMID 30354202›Full record

ArticleArteriosclerosis, thrombosis, and vascular biology2018

Associations of Circulating Protein Levels With Lipid Fractions in the General Population.

Sylwia M Figarska, Stefan Gustafsson, Johan Sundström, Johan Ärnlöv, Anders Mälarstig, Sölve Elmståhl, Tove Fall, Lars Lind, Erik Ingelsson

Open access · bronzeAbstract read
In one paragraph

Article in Arteriosclerosis, thrombosis, and vascular biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

12 citing papers in PubMed, 27 citations in OpenAlex.

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  6. Review
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  11. Cardiovascular Disease-Related Serum Proteins in Workers Occupationally Exposed to Polycyclic Aromatic Hydrocarbons.Toxicological sciences : an official journal of the Society of Toxicology · 2019
    Article
  12. Cardiometabolic Proteins Associated with Metabolic Syndrome.Metabolic syndrome and related disorders · 2019
    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

9 authors at 4 institutions in 2 countries.

Sylwia M FigarskaFrom the Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, CA (S.M.F., E.I.).
Stefan GustafssonDepartment of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory (S.G., T.F., E.I.), Uppsala University, Sweden.
Johan SundströmDepartment of Medical Sciences, Cardiovascular Epidemiology (J.S., L.L.), Uppsala University, Sweden.
Johan ÄrnlövDivision of Family Medicine and Primary Care, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Sweden (J.Ä.).
Anders MälarstigDepartment of Medicine Solna, Cardiovascular Medicine Unit, Karolinska Institutet, Stockholm, Sweden (A.M.).
Sölve ElmståhlDivision of Geriatric Medicine, Department of Clinical Sciences, Malmö University Hospital, Lund University, Sweden (S.E.).
Tove FallDepartment of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory (S.G., T.F., E.I.), Uppsala University, Sweden.
Lars LindDepartment of Medical Sciences, Cardiovascular Epidemiology (J.S., L.L.), Uppsala University, Sweden.
Erik IngelssonFrom the Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, CA (S.M.F., E.I.).
Uppsala University · SEKarolinska Institutet · SEScience for Life Laboratory · SEStanford University · US

Funding

Beyond GWAS of insulin resistance: An integrated approach to translate genetic association to functionR01DK106236 · NIDDK · STANFORD UNIVERSITY · PI KNOWLES, JOSHUA WILEY · 2016 to 2020
$2.4M
Causal associations of circulating biomarkers with cardiovascular diseaseR01HL135313 · NHLBI · STANFORD UNIVERSITY · PI INGELSSON, ERIK · 2017 to 2019
$1.6M
NHLBI NIH HHS R01 HL135313NIDDK NIH HHS R01 DK106236
6 · The paper itself

Abstract

Objective- Revealing patterns of associations between circulating protein and lipid levels could improve biological understanding of cardiovascular disease (CVD). In this study, we investigated the associations between proteins related to CVD and triglyceride (TG), total cholesterol, LDL (low-density lipoprotein), and HDL (high-density lipoprotein) cholesterol levels in individuals from the general population. Approach and Results- We measured plasma protein levels using the Olink ProSeek CVD I or II+III arrays and analyzed 57 proteins available in 3 population-based cohorts: EpiHealth (n=2029; 52% women; median age, 61 years), PIVUS (Prospective Study of the Vasculature in Uppsala Seniors; n=790; 51% women; all aged 70 years), and ULSAM (Uppsala Longitudinal Study of Adult Men; n=551; all men aged 77 years). A discovery analysis was performed in EpiHealth in a regression framework (adjusted for sex, age, body mass index, smoking, glucose levels, systolic blood pressure, blood pressure medication, diabetes mellitus medication, and CVD history), and associations with false discovery rate <0.05 were further tested in PIVUS and ULSAM, where a P value of 0.05 was considered a successful replication (validation false discovery rate of 0.1%). We used summary statistics from a genome-wide association study on each protein biomarker (meta-analysis of EpiHealth, PIVUS, ULSAM, and IMPROVE [Carotid Intima-Media Thickness and IMT-Progression as Predictors of Vascular Events in a High-Risk European Population]) and publicly available data from Global Lipids Genetics Consortium to perform Mendelian randomization analyses to address possible causality of protein levels. Of 57 tested proteins, 42 demonstrated an association with at least 1 lipid fraction; 35 were associated with TG, 15 with total cholesterol, 9 with LDL cholesterol, and 24 with HDL cholesterol. Among these associations, we found KIM-1 (kidney injury molecule-1), TNFR (TNF [tumor necrosis factor] receptor) 1 and 2, TRAIL-R2 (TRAIL [TNF-related apoptosis-inducing ligand] receptor 2), and RETN (resistin) to be associated with all 4 lipid fractions. Further, 15 proteins were related to both TG and HDL cholesterol in a consistent and biologically expected manner, that is, higher TG and lower HDL cholesterol or vice versa. Another common pattern of associations was concomitantly higher TG, total cholesterol, and LDL cholesterol, which is associated with higher CVD risk. We did not find evidence of causal links for protein levels. Conclusions- Our comprehensive analysis of plasma proteins and lipid fractions of 3370 individuals from the general population provides new information about lipid metabolism.

Indexed as

Lipid MetabolismAgedAged, 80 and overBiomarkersBlood ProteinsCholesterol, HDLCholesterol, LDLFemaleGenotypeHumansMaleMendelian Randomization AnalysisMiddle AgedPhenotypePolymorphism, Single NucleotideProtein Interaction MapsBiomarkersBlood ProteinsCholesterol, HDLCholesterol, LDLTriglyceridescholesterolhumansproteomicstriglycerides

Identifiers

PMID30354202
PMCPMC6205762
OpenAlexW2887468934

What OpenQuestion holds

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LicenceTDM
Read underepoch 390

Registered trials

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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.