ReviewGlobal heart2026
Unraveling Emerging Data on Lipoprotein(a)-Driven Cardiovascular Disease via Multiomics: A Review.
Review in Global heart, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Evidence has shown that lipoprotein(a) (Lp[a]) is an independent, causal, genetic risk factor for cardiovascular disease (CVD) that promotes the progression of high-risk, vulnerable atherosclerotic plaque phenotypes. Systems biology integrates multiomics datasets to study linear and nonlinear relationships to enhance understanding of the molecular patterns of disease. One such example is the Genetic Loci and the Burden of Atherosclerotic Lesions (GLOBAL) study, which utilizes multiomics profiling to unravel the molecular signatures of Lp(a)-driven CVD. Using deep phenotyping of coronary atherosclerosis by coronary computed tomography angiography, whole-genome sequencing for genetic analysis, and evaluation of thousands of omics measurements and circulating biomarkers, it is possible to describe the atherogenic milieu associated with Lp(a)-driven CVD. By leveraging the multiomic evaluation of Lp(a)-driven coronary phenotypes, we can begin to translate these findings into real-world strategies for earlier recognition of distinct Lp(a)-driven CVD, which may contribute to improved risk mitigation strategies in clinical practice.
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Registered trials
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.