Evidence mapPaperPMID 42365607Full record

ArticleJournal of proteome research2026

Size-Resolved Lipoprotein Fatty Acid Content as a Novel Nuclear Magnetic Resonance-Derived Trait Specifically Associates with Genetic Variants That Control Fatty Acid Metabolism.

Aziz Belkadi, Gaurav Thareja, Nisha Stephan, Anna Halama, Karsten Suhre

Abstract read
In one paragraph

Article in Journal of proteome research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Aziz BelkadiBioinformatics Core, Weill Cornell Medicine-Qatar, Education City, Doha24144, Qatar.ORCID 0000-0003-1564-0468
Gaurav TharejaBioinformatics Core, Weill Cornell Medicine-Qatar, Education City, Doha24144, Qatar.
Nisha StephanBioinformatics Core, Weill Cornell Medicine-Qatar, Education City, Doha24144, Qatar.ORCID 0000-0002-8133-2597
Anna HalamaBioinformatics Core, Weill Cornell Medicine-Qatar, Education City, Doha24144, Qatar.
Karsten SuhreBioinformatics Core, Weill Cornell Medicine-Qatar, Education City, Doha24144, Qatar.ORCID 0000-0001-9638-3912

Funding

Qatar National Research Fund ARG01-0420-230007Qatar National Research Fund PPM06-0522-230038Weill Cornell Medicine - Qatar NA
6 · The paper itself

Abstract

Population-level nuclear magnetic resonance (NMR)-based lipoprotein profiling is a key tool for investigating dysregulated lipoprotein metabolism and its role in cardiovascular disorders. However, associations with size-resolved lipoprotein composition readouts are difficult to dissect, as these traits are often highly correlated. Derived variables can therefore be more relevant to biological interpretation. Here, we show that the total fatty acid (FA) content of the lipoproteins derived from their lipid headgroup concentrations using the formula FA = 3TG + 2PL + CE strongly correlates (Spearman rho = 0.98) with the independently measured total fatty acid content. This observation is not self-evident since these variables are determined using different portions of the NMR spectrum. Using NMR data acquired on the Nightingale platform for 274,303 UK Biobank (UKB) participants and genetic associations as a readout, we then show that this relationship also holds at the size-resolved lipoprotein level. We identified eight gene loci where the proposed FA variables display a significantly stronger genetic association signal than that of the corresponding lipid headgroup variables. Five of these loci (LIPC, LIPG, PLB1, LPL, and APOC3) have a direct function in FA metabolism. Including computed size-resolved FA variables may therefore improve the biological interpretation of future studies based on Nightingale's data.

Indexed as

Fatty AcidsLipoproteinsGenetic VariationHumansLipid MetabolismMagnetic Resonance SpectroscopyUK BiobankFatty AcidsLipoproteinscholesteryl esterfatty acid metabolismlipoprotein compositionNightingale platformnuclear magnetic resonance spectroscopytriglyceridesUK Biobank

Identifiers

PMID42365607
PMCPMC13459530

What Socratic 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 Socratic graph.