Evidence map›Paper›PMID 42449406›Full record

SynthesisGenome biology2026

Genetic architecture and cross-platform validation of apolipoprotein A-IV concentrations.

Adriana Koller, Florian Schnitzer, Barbara Kollerits, Claudia Lamina, Samuel Moix, Annique Claringbould, Binisha H Mishra, Haojie Lu, Johanna F Schachtl-Riess, Lukas Forer and 16 more

Abstract readMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Genome biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

26 authors.

Adriana KollerInstitute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstrasse 3, 6020, Innsbruck, Austria.
Florian SchnitzerInstitute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstrasse 3, 6020, Innsbruck, Austria.
Barbara KolleritsInstitute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstrasse 3, 6020, Innsbruck, Austria.
Claudia LaminaInstitute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstrasse 3, 6020, Innsbruck, Austria.
Samuel MoixDepartment of Computational Biology, University of Lausanne, Lausanne, Switzerland.
Annique ClaringbouldDepartment of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands.
Binisha H MishraDepartment of Clinical Chemistry, Faculty of Medicine and Health Technology, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Tampere University, Tampere, Finland.
Haojie LuDepartment of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands.
Johanna F Schachtl-RiessInstitute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstrasse 3, 6020, Innsbruck, Austria.
Lukas ForerInstitute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstrasse 3, 6020, Innsbruck, Austria.
Christian GiegerInstitute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.
Azin KheirkhahInstitute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstrasse 3, 6020, Innsbruck, Austria.
Terho LehtimäkiDepartment of Clinical Chemistry, Faculty of Medicine and Health Technology, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Tampere University, Tampere, Finland.
Pedro Marques-VidalDepartment of Medicine, Internal Medicine, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland.
Sebastian SchönherrInstitute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstrasse 3, 6020, Innsbruck, Austria.
Klaus J StarkDepartment of Genetic Epidemiology, University of Regensburg, Regensburg, Germany.
Reinhard WürznerInstitute of Hygiene and Medical Microbiology, Medical University of Innsbruck, Innsbruck, Austria.
Kai-Uwe EckardtDepartment of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
Iris M HeidDepartment of Genetic Epidemiology, University of Regensburg, Regensburg, Germany.
Maryam KavousiDepartment of Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands.
Anna KöttgenInstitute of Epidemiology and Prevention, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.
Olli RaitakariCentre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland.
Eric J G SijbrandsDepartment of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands.
Annette PetersInstitute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.
Peter VollenweiderDepartment of Medicine, Internal Medicine, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland.
Florian KronenbergInstitute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstrasse 3, 6020, Innsbruck, Austria. Florian.Kronenberg@i-med.ac.at.ORCID https://orcid.org/0000-0003-2229-1120

Funding

Austrian Science Fund W-1253 DK HOROSTiroler Nachwuchsforscher∗innen Förderung F.50505/6-2024
6 · The paper itself

Abstract

backgroundApolipoprotein A-IV (apoA-IV) plays key roles in lipid metabolism, reverse cholesterol transport, and kidney function, yet its genetic determinants remain poorly defined. We conduct a genome-wide association study (GWAS) meta-analysis of apoA-IV concentrations measured by ELISA in 25,181 individuals and combine these with proteomic data from 33,995 UK Biobank participants (Olink platform), yielding a total sample of 59,176. We perform genetic correlations and colocalization analyses to explore links with lipid, renal, and other complex traits.

resultsThe GWAS identifies several novel loci to be associated with apoA-IV concentrations (TDRD5, DPP4, MYL3, MORC1, MCUB, GATA4, ZPR1, UMOD, GLP2R, SLC38A10 and APOE) besides two previously identified loci (APOA5-A4-C3-A1 cluster and KLKB1). Cross-platform comparison shows strong concordance of effect directions and magnitudes, underscoring the robustness of findings across measurement techniques. Global genetic correlation reveals significant shared genetic architecture between apoA-IV, kidney function and HDL-cholesterol, while colocalization supports shared causal variants with lipid, renal, and hematological phenotypes, suggesting biologically relevant pathways.

conclusionThese results provide a comprehensive overview of the genetic architecture of apoA-IV and suggest mechanistic links to lipid metabolism, kidney function and blood-related traits. Our findings refine the role of apoA-IV as a potential biomarker and inform future epidemiological research.

Indexed as

Apolipoproteins AGenome-Wide Association StudyHumansLipid MetabolismPhenotypePolymorphism, Single NucleotideQuantitative Trait Lociapolipoprotein A-IVApolipoproteins AApolipoprotein A-IVGenetic correlationGWASKidney functionLipid traits

Identifiers

PMID42449406
PMCPMC13647689

What OpenQuestion holds

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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.