【Nature】Nonalcoholic fatty liver disease large-scale multi-omics study found drug targets and biomarkers

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Written by Lily

Nonalcoholic fatty liver disease (NAFLD) has not been approved for specific drug treatment; Therefore, in order to monitor disease progression and treatment response, there is an urgent need to identify potential drug targets and biomarkers for
NAFLD.
Recently, a research team from the University of Iceland conducted a large-scale genome-wide association study of NAFLD, identifying sequence variants associated with NAFLD – including rare protective loss-of-function variants pointing to potential drug targets; A model that can distinguish between NAFL and cirrhosis was constructed using proteomic data, providing a non-invasive tool
for the diagnosis and evaluation of NAFLD.

Nonalcoholic fatty liver disease (NAFLD)

 01 

Nonalcoholic fatty liver disease (NAFLD), which affects about a quarter of the world's population, has become a growing health problem
.
Nonalcoholic fatty liver (NAFL) is the first stage of NAFLD – when fat accumulation occurs by unexplained causes (other than excessive alcohol consumption or other definite liver damaging factors) account for 5% or more
of the entire liver.
NAFL can progress to nonalcoholic steatohepatitis (NASH); More seriously, some patients with NASH can further develop cirrhosis and hepatocellular carcinoma (HCC).

Obesity, metabolic syndrome, diabetes, and hypertension are recognized risk factors for NAFL and NASH; Cirrhosis associated with NASH is the second most common indication for liver transplantation
.

The diagnosis and staging of NAFLD is challenging: although elevated liver enzymes are a common manifestation of NAFLD, liver enzymes are nonspecific and do not predict NAFLD progression
well.
Although the proton density fat fraction (PDFF) derived from magnetic resonance imaging (MRI) can accurately quantify liver fat; However, liver biopsy remains essential for the diagnosis and staging of nonalcoholic fatty liver disease (NASH) – unfortunately, biopsy can involve sampling variability and the risk of
complications.
Currently, there are no specific drugs for NASH that have been approved; Therefore, in order to monitor disease progression and treatment response, there is an urgent need to identify potential drug targets and biomarkers for
NAFLD.

Large genome-wide association study of NAFLD

 02 

On October 24, a team of researchers from the University of Iceland published a research paper
entitled "Multiomics study of nonalcoholic fatty liver disease" in the journal Nature Genetics 。 The study conducted a large-scale genome-wide association study of nonalcoholic steatohepatitis (NASH), cirrhosis, and hepatocellular carcinoma (HCC), identifying sequence variants associated with NAFLD—including rare, protective loss-of-function variants pointing to potential drug targets
.

In addition, through plasma proteomics analysis, this study revealed the pathogenesis of NAFLD, and then identified potential biomarkers of disease, disease progression, and target binding.
A model that can distinguish between NAFL and cirrhosis was constructed using proteomic data, providing a non-invasive tool
for the diagnosis and evaluation of NAFLD.

style="box-sizing: border-box;" _msthash="251146" _msttexthash="198614">GWAS analysis

 03 

Regarding NAFL, the investigators used 9,491 clinical cases and proton density fat fraction (PDFF)
extracted from 36,116 liver magnetic resonance images.
MR images were generated using two acquisition techniques: 8,448 images were generated using gradient multiple echo (GRE); An iterative hydrolipid separation image (IDEAL) using echo asymmetry and least squares generated 27,668 images
.
20.
0% of IDEAL images and 23.
6% of GRE images had a proton density fat fraction (PDFF) >5%.

Of the 270 (IDEAL) and 97 (GRE) individuals diagnosed with NAFL, 179 (66.
3%) and 76 (78.
4%) had a PDFF > 5.
0%,
respectively.
The PDFF estimate in this study correlated well with 3,869 PDFF values calculated using LiverMultiScan26 (r2=0.
96).

Figure 1.
Distribution of PDFF estimates:

The research team conducted a genome-wide association study (GWAS) of the PDFF estimate (n=36,116)
using the first available MRI measurement for each individual.
In addition, a meta-analysis of GWAS was performed for 9,491 cases clinically diagnosed with NAFL – 785 from Iceland (deCODE genetics database), 5,921 from the UK (UK Biobank database), and 2,134 from the United States (Intermountain INSPIRE and HerediGene database).

The same analysis
was performed in the 876,210 control group.

This study identified 18 independent sequence variants at 17 sites in GWAS analysis, four of which have not been reported in previous NAFL-related GWAS analyses (in or near PNPLA2, TOR1B, APOH, and GUSB).

The effects of these variants on both phenotypes are comparable, meaning that variants that increase PDFF values also increase the risk of NAFL and vice versa
.

Figure 2.
Effects of sequence variation on PDFF compared to effects on liver disease, liver enzymes, and lipids:

Research findings and significance

 04 

Eighteen sequence variants associated with NAFL and four associated with cirrhosis were identified; And rare, predictive loss-of-protection variants were found in MTARC1 and GPAM—highlighting them as potential drug targets
.

By looking at associations with 52 other phenotypes and traits, the study explored the pleiotropic effects
of identified variants.
BMI is one of the most common risk factors for NAFLD, and longitudinal PDFF measurements suggest that carriers of p.
ile148Met, a well-known NAFLD risk variant, in PNPLA3 are more susceptible to changes in BMI than non-carriers
.

To investigate whether plasma proteins can effectively distinguish between NAFL and cirrhosis, liver enzymes, age, sex, and BMI were used as baselines, and punitive logistic regression models
were trained using plasma proteomes and genetic risk scores (GRSs).
The study showed that models trained with plasma proteomes performed better than other models
in distinguishing between NAFL and cirrhosis, NAFL and the general population, and cirrhosis and the general population in Iceland and the UK Biobank cohort.

This study used multiomics data to elucidate the genetic basis of NAFLD, and analysis of predicted LoF (pLOF) variants, blood RNA expression, and plasma proteomics data pointed to whether changes in disease-causing genes and their functions contribute to pathogenesis
.
At the same time, the different effects of NAFL risk alleles on other diseases and traits, including blood lipids and proteins, were demonstrated, and plasma proteomics had the potential to
stage NAFLD.
This study is one of the largest conducted to date to elucidate the genetic basis of NAFLD, and its results are expected to help develop diagnostic tools or therapies
for NAFLD.

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style="white-space: normal;box-sizing: border-box;">Note: This article is intended to introduce the progress of medical research and cannot be used as a reference
for treatment options.
If you need health guidance, please go to a regular hospital
.