Evidence mapPaperPMID 41787643Full record

ArticleJournal of clinical laboratory analysis2026

Lipid Profile Alterations Across Coronary Heart Disease, Metabolic Syndrome, and Nephrotic Syndrome.

Shudong Tan, Tianji Qu, Jing Ai, Yaoyang Fu

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Article in Journal of clinical laboratory analysis, 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

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Shudong TanDepartment of Clinical Laboratory, The Fifth Affiliated Hospital of Sun Yat-Sen University, Zhuhai, China.
Tianji QuDepartment of Clinical Laboratory, The Fifth Affiliated Hospital of Sun Yat-Sen University, Zhuhai, China.
Jing AiDepartment of Clinical Laboratory, Zhejiang Provincial People's Hospital, Hangzhou, China.
Yaoyang FuDepartment of Clinical Psychology, Hangzhou First People's Hospital, Hangzhou, China.ORCID https://orcid.org/0000-0002-4961-0374

Funding

Joint Fund of Zhejiang Provincial Natural Science Foundation of China LHZY24H090005Medical and Health Research Project of Zhejiang Province 2025KY1060
6 · The paper itself

Abstract

backgroundDyslipidemia was a hallmark of metabolic disturbances in coronary heart disease (CHD), metabolic syndrome (MetS), and nephrotic syndrome (NS), yet the specific lipid profile patterns characteristic of each disease remained insufficiently defined.

objectiveThis study aimed to clearly characterize and compare the qualitative features of lipid profiles across patients with CHD, MetS, and NS, and to identify key lipid markers associated with disease classification using multinomial logistic regression.

methodsA total of 180 patients were enrolled and classified into three groups (CHD, MetS, NS) based on established diagnostic criteria. 60 healthy controls were concurrently enrolled. Lipidomic profiles and additional laboratory parameters were measured using validated analytical methods. Multinomial logistic regression was used to evaluate the associations between lipid parameters and disease categories.

resultsLipid profile analysis revealed distinct qualitative trends across the disease groups. The CHD group demonstrated notably higher levels of TC and sdLDL, the MetS group exhibited prominent increases in TG and ApoE, while the NS group showed a broad and pronounced elevation across most measured lipid parameters. By contrast, the healthy control group consistently presented uniformly lower lipid levels. LASSO-guided multinomial logistic regression identified TC, TG, ApoB, ApoE, and sdLDL-C as independent predictors of disease classification.

conclusionsDistinct patterns of dyslipidemia were observed in CHD, MetS, and NS. TC and sdLDL-C might serve as robust markers for CHD, while ApoB demonstrated disease-specific variability with diagnostic potential. These findings underscored the importance of detailed lipid profiling for improved risk stratification and targeted management.

Indexed as

Coronary DiseaseLipidsMetabolic SyndromeNephrotic SyndromeAgedBiomarkersCase-Control StudiesFemaleHumansMaleMiddle AgedBiomarkersLipidscoronary heart diseasedyslipidemiametabolic syndromenephrotic syndrome

Identifiers

PMID41787643
PMCPMC13051875

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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.