Identification of Novel Metabolic Subtypes Using Multi-Trait Limited Mixed Regression in the Chinese Population.

ABSTRACT: The aggregation and interaction of metabolic risk factors leads to highly heterogeneous pathogeneses, manifestations, and outcomes, hindering risk stratification and targeted management. To deconstruct the heterogeneity, we used baseline data from phase II of the Fangshan Family-Based Ischemic Stroke Study (FISSIC), and a total of 4632 participants were included. A total of 732 individuals who did not have any component of metabolic syndrome (MetS) were set as a reference group, while 3900 individuals with metabolic abnormalities were clustered into subtypes using multi-trait limited mixed regression (MFMR). Four metabolic subtypes were identified with the dominant characteristics of abdominal obesity, hypertension, hyperglycemia, and dyslipidemia. Multivariate logistic regression showed t

SUBMITTER: Ding K 

PROVIDER: S-EPMC9775185 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature