期刊
CIRCULATION RESEARCH
卷 128, 期 3, 页码 309-320出版社
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1161/CIRCRESAHA.120.317883
关键词
biomarker; heart failure; metabolism; lipidomics; lipids
资金
- National Institutes of Health [R01HL118264, R01DK102896]
- official funding agency for biomedical research of the Spanish government
- Instituto de Salud Carlos III [RTIC G03/140, RTIC RD 06/0045]
- Instituto de Salud Carlos III through the Centro de Investigacion Biomedica en Red de Fisiopatologia de la Obesidad y Nutricion
- Fondo de Investigacion Sanitaria-Fondo Europeo de Desarrollo Regional [PI04-2239, PI 05/2584, CP06/00100, PI07/0240, PI07/1138, PI07/0954, PI 07/0473, PI10/01407, PI10/02658, PI11/01647, P11/02505, PI13/00462]
- Ministerio de Ciencia e Investigacion [AGL-2009-13906-C02, AGL2010-22319-C03]
- Fundacion Mapfre 2010, Consejeria de Salud de la Junta de Andalucia [PI0105/2007]
- Public Health Division of the Department of Health of the Autonomous Government of Catalonia, Generalitat Valenciana [ACOMP06109, GVA-COMP2010-181, GVACOMP2011-151, CS2010-AP-111, CS2011AP-042]
- Regional Government of Navarra [P27/2011]
- Federal Ministry of Science, Germany [01 EA 9401]
- European Union [SOC 95201408 05F02]
- German Cancer Aid [70-2488-Ha I]
- European Community [SOC 98200769 05F02]
- German Ministry of Education and Research (BMBF)
- State of Brandenburg (DZD) [82DZD00302]
- ICREA
- German Research Foundation (DFG)
- Centro Nacional de Investigaciones Cardiovasculares [CNIC 06/2007]
- European Union
- Cardiometabolic Health (FAME)-consortium [01EA1704]
This study identified and validated two lipid metabolites and several lipidomics patterns as potential novel biomarkers of HF risk. Lipid profiling may capture preclinical molecular alterations that predispose to incident HF.
RATIONALE: Altered lipid metabolism has been implicated in heart failure (HF) development, but no prospective studies have examined comprehensive lipidomics data and subsequent risk of HF. OBJECTIVE: We aimed to link single lipid metabolites and lipidomics networks to the risk of developing HF. METHODS AND RESULTS: Discovery analyses were based on 216 targeted lipids in a case-control study (331 incident HF cases and 507 controls, matched by age, sex, and study center), nested within the PREDIMED (Prevencion con Dieta Mediterranea) study. Associations of single lipids were examined in conditional logistic regression models. Furthermore, lipidomics networks were linked to HF risk in a multistep workflow, including machine learning-based identification of the HF-related network clusters, and regression-based discovery of the HF-related lipid patterns within these clusters. If available, significant findings were externally validated in a subsample of the EPIC-Potsdam cohort (2414 at-risk participants, including 87 incident HF cases). After confounder-adjustments, 2 lipids were significantly associated with HF risk in both cohorts: CER (ceramide) 16:0 (relative risk [RR] per SD in PREDIMED, 1.28 [95% CI, 1.13-1.47]) and phosphatidylcholine 32_0 (RR per SD in PREDIMED, 1.23 [95% CI, 1.08-1.41]). Additionally, lipid patterns in several network clusters were associated with HF risk in PREDIMED. Adjusted for standard risk factors, an internally cross-validated score based on the significant HF-related lipids that were identified in the network analysis in PREDIMED was associated with a higher HF risk (20 lipids, RR per SD, 2.33 [95% CI, 1.93%-2.81%). Moreover, a lipid score restricted to the externally available lipids was significantly associated with HF incidence in both cohorts (6 lipids, RRs per SD, 1.30 [95% CI, 1.14-1.47] in PREDIMED, and 1.46 [95% CI, 1.17-1.82] in EPIC-Potsdam). CONCLUSIONS: Our study identified and validated 2 lipid metabolites and several lipidomics patterns as potential novel biomarkers of HF risk. Lipid profiling may capture preclinical molecular alterations that predispose for incident HF.
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