Active Genetics & Molecular Biology Lungs & Breathing

Discovery of NAFLD gene regulatory networks with multi-omics

In plain English

AI plain-English summary

A liver biopsy is not just a piece of tissue—it is a library of genetic instructions gone wrong, and this project will read them cell by cell. Non-alcoholic fatty liver disease (NAFLD) affects roughly one in four adults worldwide, yet no drug exists to stop it. The problem is that scientists do not know which genetic switches in which liver cells actually drive the disease. Current maps are too blurry to tell a sick hepatocyte from a healthy one at the level of gene regulation. This project fills that gap by applying single-cell multi-omics—a technique that measures both gene activity and its regulatory elements in individual cells—to a cohort of human liver biopsies spanning early to advanced NAFLD. If successful, this work will produce the first high-resolution atlas of the gene regulatory networks that control fat accumulation in human liver cells. It will pinpoint which cell populations are most disrupted, which transcription factors orchestrate the damage, and which noncoding genetic variants are truly causal. That could transform how pharmaceutical companies and clinicians interpret risk variants from genome-wide association studies, turning statistical signals into testable drug targets. Because the project uses human cells and unbiased genetic screens, its findings are directly relevant to human biology—not just mouse models. The immediate impact is fundamental: a mechanistic understanding of why some livers fail and others do not.

View original technical description
This project will identify the cis-regulatory networks that operate in non-alcoholic fatty liver disease (NAFLD) and characterise their role in hepatocyte lipidomic traits. - I will carry out single-cell multi-omics in a cohort of liver biopsies representing different stages of NAFLD progression to identify the active genes and corresponding cis-regulatory elements with unprecedented resolution. I will: - identify the hepatic cell populations that are mostly altered in different degrees of NAFLD and their corresponding marker genes; - identify the transcription factors that drive the transcriptional/phenotypical changes detected with NAFLD progression; - pinpoint the hepatic cell populations whose genetic disruption contributes the most to the heritability of NAFLD and/or NAFLD-associated traits. - To gain mechanistic insights into the contribution of specific genetic loci to NAFLD risk, I will: - carry out variant level in silico and experimental analyses to prioritise variants likely to be causal; - use the single-cell multi-omic maps to assign noncoding NAFLD risk variants to target genes in specific hepatic cell populations ('NAFLD genes'); - perform an unbiased loss-of-function genetic screen to identify 'NAFLD genes' that affect intracellular lipid morphological features in human hepatocytes; - use gain/loss-of-function models (regulatory variant and gene levels) in human hepatocytes to validate findings and further characterise hits from the genetic screen.

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Researchers

Cebola (EPMC Awardee)

Related Research

Grants with similar aims, by meaning.

Investigation of NAFLD-associated epigenetic dysregulation
Multiomic Analysis of the Hepatic Fibrotic Niche to Define New Therapeutic Targets for Liver Scarring
Molecular Resolution of Human NAFLD/Cirrhosis Using Single Cell RNA Sequencing: Identification and Validation of Novel Fibrotic and Disease Targets
Elucidating Pathways of Steatohepatitis as part of the NAFLD project
Analysis of patient-derived tissues to characterise the spectrum of NAFLD to establish mechanisms driving liver disease, enhance biomarker identification and drug discovery.

Original classification

Sir Henry Dale Fellowship

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