A Microphysiological Model of Progressive Human Hepatic Insulin Resistance

Overview

Journal bioRxiv

Date 2025 Jan 20

PMID 39829839

Authors

Dominick J Hellen

Jessica Ungerleider

Erin Tevonian

Pierre Sphabmixay

Priyatanu Roy

Caroline Lewis

Jacob Jeppesen

Damien Demozay

Linda G Griffith

Affiliations

Soon will be listed here.

Abstract

Background & Aims: Hepatic insulin resistance is a fundamental phenomenon observed in both Type 2 diabetes (T2D) and metabolic (dysfunction) associated fatty liver disease (MAFLD). The relative contributions of nutrients, hyperinsulinemia, hormones, inflammation, and other cues are difficult to parse as they are convoluted by interplay between the local and systemic events. Here, we used a well-established human liver microphysiological system (MPS) to establish a physiologically-relevant insulin-responsive metabolic baseline and probe how primary human hepatocytes respond to controlled perturbations in insulin, glucose, and free fatty acids (FFAs).

Methods: Replicate liver MPS were maintained in media with either 200 pM (normal) or 800 pM (T2D) insulin for up to 3 weeks. Conditions of standard glucose (5.5 mM), hyperglycemia (11 mM glucose), normal (20μM) and elevated FFA (100 μM), alone and in combination were used at each insulin concentration, either continuously or reversing back to standard media after 2 weeks of simulated T2D conditions. Hepatic glucose production, activation of signaling pathways, insulin clearance, transcriptome analysis, and intracellular lipid and bile acid accumulation were assessed.

Results: Hyperinsulinemia alone induces insulin resistance after one week of exposure, while hyperglycemia and increased FFAs significantly exacerbate this phenotype. Hyperinsulinemia, along with elevated glucose and FFAs, transcriptionally predisposes hepatocytes to insulin resistance through altered metabolic and immune signaling pathways. The phenotypes observed in hyperinsulinemia and nutrient overload are partially reversible upon return to normophysiologic conditions.

Conclusions: Our enhanced model, replicating multiple aspects of the insulin-resistant condition, offers improved insights into disease mechanisms with relevance to human physiology.

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