Metabolite Signature of Life's Essential 8 and Risk of Coronary Heart Disease Among Low-Income Black and White Americans.

cardiovascular health coronary heart disease life’s essential 8 metabolomics multiracial population

Journal

Circulation. Genomic and precision medicine
ISSN: 2574-8300
Titre abrégé: Circ Genom Precis Med
Pays: United States
ID NLM: 101714113

Informations de publication

Date de publication:
28 Nov 2023
Historique:
medline: 28 11 2023
pubmed: 28 11 2023
entrez: 28 11 2023
Statut: aheadofprint

Résumé

Life's essential 8 (LE8) is a comprehensive construct of cardiovascular health. Yet, little is known about the LE8 score, its metabolic correlates, and its predictive implications among Black Americans and low-income individuals. In a nested case-control study of coronary heart disease (CHD) among 299 pairs of Black and 298 pairs of White low-income Americans from the Southern Community Cohort Study, we estimated LE8 score and applied untargeted plasma metabolomics and elastic net with leave-one-out cross-validation to identify metabolite signature (MetaSig) of LE8. Associations of LE8 score and MetaSig with incident CHD were examined using conditional logistic regression. The mediation effect of MetaSig on the LE8-CHD association was also examined. The external validity of MetaSig was evaluated in another nested CHD case-control study among 299 pairs of Chinese adults. Higher LE8 score was associated with lower CHD risk (standardized odds ratio, 0.61 [95% CI, 0.53-0.69]). The MetaSig, consisting of 133 metabolites, showed significant correlation with LE8 score ( Higher LE8 score and its MetaSig were associated with lower CHD risk among low-income Black and White Americans. Metabolomics may offer an objective measure of LE8 and its metabolic phenotype relevant to CHD prevention among diverse populations.

Sections du résumé

BACKGROUND UNASSIGNED
Life's essential 8 (LE8) is a comprehensive construct of cardiovascular health. Yet, little is known about the LE8 score, its metabolic correlates, and its predictive implications among Black Americans and low-income individuals.
METHODS UNASSIGNED
In a nested case-control study of coronary heart disease (CHD) among 299 pairs of Black and 298 pairs of White low-income Americans from the Southern Community Cohort Study, we estimated LE8 score and applied untargeted plasma metabolomics and elastic net with leave-one-out cross-validation to identify metabolite signature (MetaSig) of LE8. Associations of LE8 score and MetaSig with incident CHD were examined using conditional logistic regression. The mediation effect of MetaSig on the LE8-CHD association was also examined. The external validity of MetaSig was evaluated in another nested CHD case-control study among 299 pairs of Chinese adults.
RESULTS UNASSIGNED
Higher LE8 score was associated with lower CHD risk (standardized odds ratio, 0.61 [95% CI, 0.53-0.69]). The MetaSig, consisting of 133 metabolites, showed significant correlation with LE8 score (
CONCLUSIONS UNASSIGNED
Higher LE8 score and its MetaSig were associated with lower CHD risk among low-income Black and White Americans. Metabolomics may offer an objective measure of LE8 and its metabolic phenotype relevant to CHD prevention among diverse populations.

Identifiants

pubmed: 38014580
doi: 10.1161/CIRCGEN.123.004230
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e004230

Commentaires et corrections

Type : UpdateOf

Auteurs

Kui Deng (K)

Department of Medicine, Vanderbilt Epidemiology Center and Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN. (K.D., X.-O.S., L.L., W.Z., H.C., Q.C., D.Y.).

Deepak K Gupta (DK)

Department of Medicine, Vanderbilt Translational and Clinical Cardiovascular Research Center and Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN. (D.K.G., V.E.T.).

Xiao-Ou Shu (XO)

Department of Medicine, Vanderbilt Epidemiology Center and Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN. (K.D., X.-O.S., L.L., W.Z., H.C., Q.C., D.Y.).

Loren Lipworth (L)

Department of Medicine, Vanderbilt Epidemiology Center and Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN. (K.D., X.-O.S., L.L., W.Z., H.C., Q.C., D.Y.).

Wei Zheng (W)

Department of Medicine, Vanderbilt Epidemiology Center and Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN. (K.D., X.-O.S., L.L., W.Z., H.C., Q.C., D.Y.).

Victoria E Thomas (VE)

Department of Medicine, Vanderbilt Translational and Clinical Cardiovascular Research Center and Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN. (D.K.G., V.E.T.).

Hui Cai (H)

Department of Medicine, Vanderbilt Epidemiology Center and Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN. (K.D., X.-O.S., L.L., W.Z., H.C., Q.C., D.Y.).

Qiuyin Cai (Q)

Department of Medicine, Vanderbilt Epidemiology Center and Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN. (K.D., X.-O.S., L.L., W.Z., H.C., Q.C., D.Y.).

Thomas J Wang (TJ)

Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas (T.J.W.).

Danxia Yu (D)

Department of Medicine, Vanderbilt Epidemiology Center and Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN. (K.D., X.-O.S., L.L., W.Z., H.C., Q.C., D.Y.).

Classifications MeSH