Evidence map›Paper›PMID 40157129›Full record

ArticleEBioMedicine2025

Examining the link between 179 lipid species and 7 diseases using genetic predictors.

Linda Ottensmann, Rubina Tabassum, Sanni E Ruotsalainen, Mathias J Gerl, Christian Klose, Daniel L McCartney, Elisabeth Widén, FinnGen, Kai Simons, Samuli Ripatti and 3 more

Abstract read
In one paragraph

Article in EBioMedicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Observational
  2. 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

13 authors.

Linda OttensmannInstitute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland; Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom. Electronic address: linda.ottensmann@helsinki.fi.
Rubina TabassumInstitute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland.
Sanni E RuotsalainenInstitute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland.
Mathias J GerlLipotype GmbH, Dresden, Germany.
Christian KloseLipotype GmbH, Dresden, Germany.
Daniel L McCartneyCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom.
Elisabeth WidénInstitute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland.
FinnGen
Kai SimonsLipotype GmbH, Dresden, Germany.
Samuli RipattiInstitute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland; Department of Public Health, Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland; Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA.
Veronique VitartMedical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom.
Caroline HaywardMedical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom.
Matti PirinenInstitute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland; Department of Public Health, Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland; Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland. Electronic address: matti.pirinen@helsinki.fi.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGenome-wide association studies of lipid species have identified several loci shared with various diseases, however, the relationship between lipid species and disease risk remains poorly understood. Here we investigated whether the plasma levels of lipid species are causally linked to disease risk.

methodsWe built genetic predictors of 179 lipid species, measured in 7174 Finnish individuals, by utilising either 11 high-impact genomic loci or genome-wide polygenic scores (PGS). We assessed the impact of the lipid species on seven diseases by performing disease association across FinnGen (n = 500,348), UK Biobank (n = 420,531), and Generation Scotland (n = 20,032). We performed univariable Mendelian randomisation (MR) and multivariable MR (MVMR) analyses to examine whether lipid species impact disease risk independently of standard lipids.

findingsPGS explained >4% of the variance for 34 lipid species but variants outside the high-impact loci had only a marginal contribution. Variants within the high-impact loci showed association with all seven diseases. MVMR supported a causal role of ApoB in ischaemic heart disease after accounting for lipid species. Phosphatidylethanolamine-increasing LIPC variants seemed to lower age-related macular degeneration risk independently of HDL-cholesterol. MVMR suggested a protective effect of four lipid species containing arachidonic acid on cholelithiasis risk independently of Total Cholesterol.

interpretationOur study demonstrates how genetic predictors of lipid species can be utilised to gain insights into disease risk. We report potential links between lipid species and age-related macular degeneration and cholelithiasis risk, which can be explored for their utility in disease risk prediction and therapy.

fundingThe funders had no role in the study design, data analyses, interpretation, or writing of this article.

Indexed as

Genetic Predisposition to DiseaseLipid MetabolismLipidsFemaleFinlandGenome-Wide Association StudyHumansMaleMendelian Randomization AnalysisMiddle AgedMultifactorial InheritancePolymorphism, Single NucleotideRisk FactorsLipidsDisease riskGWASLipidomicsMendelian randomisationPGS

Identifiers

PMID40157129
PMCPMC11995710

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.