Evidence mapPaperPMID 33449144Full record

ReviewCellular and molecular life sciences : CMLS2021

Integrating lipidomics and genomics: emerging tools to understand cardiovascular diseases.

Rubina Tabassum, Samuli Ripatti

Open access · hybridAbstract readReview
In one paragraph

Review in Cellular and molecular life sciences : CMLS, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 1 pooled it
4.0field-weighted citation impact, top 5% 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

44 citing papers in PubMed, 1 synthesis or guideline pooled it, 66 citations in OpenAlex.

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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

2 authors at 2 institutions in 2 countries.

Rubina TabassumInstitute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, PO Box 20, 00014, Helsinki, Finland. rubina.tabassum@helsinki.fi.ORCID http://orcid.org/0000-0002-3120-3041
Samuli RipattiInstitute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, PO Box 20, 00014, Helsinki, Finland. samuli.ripatti@helsinki.fi.
Broad Institute · USUniversity of Helsinki · FI

Funding

Academy of Finland 312062
6 · The paper itself

Abstract

Cardiovascular diseases (CVDs) are the leading cause of mortality and morbidity worldwide leading to 31% of all global deaths. Early prediction and prevention could greatly reduce the enormous socio-economic burden posed by CVDs. Plasma lipids have been at the center stage of the prediction and prevention strategies for CVDs that have mostly relied on traditional lipids (total cholesterol, total triglycerides, HDL-C and LDL-C). The tremendous advancement in the field of lipidomics in last two decades has facilitated the research efforts to unravel the metabolic dysregulation in CVDs and their genetic determinants, enabling the understanding of pathophysiological mechanisms and identification of predictive biomarkers, beyond traditional lipids. This review presents an overview of the application of lipidomics in epidemiological and genetic studies and their contributions to the current understanding of the field. We review findings of these studies and discuss examples that demonstrates the potential of lipidomics in revealing new biology not captured by traditional lipids and lipoprotein measurements. The promising findings from these studies have raised new opportunities in the fields of personalized and predictive medicine for CVDs. The review further discusses prospects of integrating emerging genomics tools with the high-dimensional lipidome to move forward from the statistical associations towards biological understanding, therapeutic target development and risk prediction. We believe that integrating genomics with lipidome holds a great potential but further advancements in statistical and computational tools are needed to handle the high-dimensional and correlated lipidome.

Indexed as

Cardiovascular DiseasesCeramidesFatty Acid DesaturasesGenomicsHumansLife StyleLipid MetabolismLipidomicsLipidsRisk FactorsCeramidesFatty Acid DesaturasesLipidsBiomarkersDisease riskGenome-wide association studiesLipid speciesPathophysiology

Identifiers

PMID33449144
PMCPMC8004487
OpenAlexW3124029240

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.