ArticleBiomolecules2022
Integrated Quantitative Targeted Lipidomics and Proteomics Reveal Unique Fingerprints of Multiple Metabolic Conditions.
Article in Biomolecules, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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.
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Who cites it
7 citing papers in PubMed, 10 citations in OpenAlex.
- Associations of apolipoprotein A1, apolipoprotein B, and their ratio with novel cardiometabolic indices in adults with coronary artery disease.Frontiers in cardiovascular medicine · 2026Article
- Plasma Lipidomics and Proteomics Analyses Pre- and Post-5000 m Race in Yili Horses.Animals : an open access journal from MDPI · 2025Article
- Golgi-derived extracellular vesicle production induced by SARS-CoV-2 envelope protein.Apoptosis : an international journal on programmed cell death · 2025Article
- Association between cardiometabolic index and all-cause and cause-specific mortality among the general population: NHANES 1999-2018.Lipids in health and disease · 2024Article
- Review
- Serum and urine lipidomic profiles identify biomarkers diagnostic for seropositive and seronegative rheumatoid arthritis.Frontiers in immunology · 2024Article
- Chewing the fat: How lipidomics is changing our understanding of human health and disease in 2022.Analytical science advances · 2023Review
Corrections and comments
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aberrations in lipid and lipoprotein metabolic pathways can lead to numerous diseases, including cardiovascular disease, diabetes, neurological disorders, and cancer. The integration of quantitative lipid and lipoprotein profiling of human plasma may provide a powerful approach to inform early disease diagnosis and prevention. In this study, we leveraged data-driven quantitative targeted lipidomics and proteomics to identify specific molecular changes associated with different metabolic risk categories, including hyperlipidemic, hypercholesterolemic, hypertriglyceridemic, hyperglycemic, and normolipidemic conditions. Based on the quantitative characterization of serum samples from 146 individuals, we have determined individual lipid species and proteins that were significantly up- or down-regulated relative to the normolipidemic group. Then, we established protein-lipid topological networks for each metabolic category and linked dysregulated proteins and lipids with defined metabolic pathways. To evaluate the differentiating power of integrated lipidomics and proteomics data, we have built an artificial neural network model that simultaneously and accurately categorized the samples from each metabolic risk category based on the determined lipidomics and proteomics profiles. Together, our findings provide new insights into molecular changes associated with metabolic risk conditions, suggest new condition-specific associations between apolipoproteins and lipids, and may inform new biomarker discovery in lipid metabolism-associated disorders.
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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 OpenQuestion graph.