Simon Pfisterer, Finland

University of Helsinki Anatomy

Presenter of 1 Presentation

Heterogeneity of LDL Uptake Responses in Individual Hypercholesterolemia Patients

Session Type
Track 2 - Metabolism of Lipids and Lipoproteins
Date
07.10.2020, Wednesday
Session Time
10:00 - 11:13
Lecture Time
10:23 - 10:33

Abstract

Background and Aims

Despite widespread genetic analyses, we understand little of how hypercholesterolemia evolves differently in individual patients. Cellular LDL receptor (LDLR) expression, translocation to the cell surface and ultimately LDL internalization governs clearance of blood LDL. Currently, we cannot readily measure these parameters from individual patients due to high cost and long turnaround times. We set up an automated platform that allows dissection of these cellular pathways in primary human cells with improved efficiency.

Methods

We established a multi-parametric imaging platform for primary human peripheral blood mononuclear cells. This allows us to quantify LDLR surface abundance, LDL uptake and lipid storage at the single cell level from the same samples. We studied individuals with verified LDLR mutations from the METSIM (METabolic Syndrome In Men) cohort as well as hypercholesterolemic individuals lacking LDLR mutations from the FINRISK 2012 cohort. Up to date, we have analysed >60 patient samples.

Results

First, we show that our analysis of primary cells is superior to their immortalized counterparts, which display altered cellular lipid metabolism. For each patient we can quantify multiple cell populations with different LDL internalization rates under basal and stimulated conditions. We observe substantial differences in LDL internalization and LDLR surface abundance in individuals bearing identical mutations in the LDLR gene. Additionally, we demonstrate that individuals without LDLR mutations may have decreased LDL uptake. Reduced LDL uptake is often accompanied by increased cellular lipid storage, indicative of reprogrammed lipid metabolism.

Conclusions

Automated profiling provides novel insights into disease mechanisms for individual patients and will be of diagnostic value.

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