Methods for estimating insulin resistance from untargeted metabolomics data.

ABSTRACT:

Context

Insulin resistance is associated with multiple complex diseases; however, precise measures of insulin resistance are invasive, expensive, and time-consuming.

Objective

Develop estimation models for measures of insulin resistance, including insulin sensitivity index (SI) and homeostatic model assessment of insulin resistance (HOMA-IR) from metabolomics data.

Design

Insulin Resistance Atherosclerosis Family Study (IRASFS).

Setting

Community based.

Participants

Mexican Americans (MA) and African Americans (AA).

Main outcome

Estimation models for measures of insulin resistance, i.e. SI and HOMA-IR.

Results

Least Absolute Shrinkage and Selection Operator (LASSO) and Elastic Net regression were used to build insulin resistance estimation

SUBMITTER: Hsu FC 

PROVIDER: S-EPMC10412652 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature