Rare and protective loss-of-function mutations offer possible NAFLD drug targets

A significant genome-wide association study on the nonalcoholic fatty liver disease (NAFLD) has just been published in Nature Genetics by researchers from Amgen subsidiary deCODE Genetics.

Rare and protective loss-of-function mutations offer possible NAFLD drug targets
Kari Stefansson, CEO of deCODE genetics and senior author on the paper, and Gardar Sveinbjornsson, first author on the paper. Image Credit: deCODE Genetics

Identifying sequence variations linked to NAFLD included rare protective loss-of-function variants that suggest prospective drug targets. Using plasma proteome analysis, researchers could learn more about the pathophysiology of NAFLD.

Up to 25% of people worldwide could be affected by NAFLD, a significant health problem. The initial stage of NAFLD is nonalcoholic fatty liver (NAFL), which occurs when the liver is over 5% fat without any known reasons, such as drinking too much alcohol.

NAFL can develop into non-alcoholic steatohepatitis (NASH), which can progress to liver cirrhosis and hepatocellular carcinoma (HCC). NAFLD can be challenging to diagnose and keep track of, and there is no treatment at this time. Therefore, it is crucial to identify potential drug targets and biomarkers.

The results of a significant genome-wide association analysis of NAFL, liver cirrhosis, and HCC were combined with expression and proteomic data. Proton density fat fraction (PDFF) derived from 36,116 liver MRIs was also used for NAFL, in addition to 9,491 clinical cases from Finland, the UK, Iceland, and the United States.

Rare, protective, predicted loss-of-function sequence variants in MTARC1 and GPAM were found in the Icelandic population, which suggests that suppressing MTARC1 or GPAM could be therapeutic for NAFL or NASH.

It was possible to uncover potential biomarkers of the disease, disease progression, or target engagement by analyzing the levels of thousands of proteins detected in plasma. Proteomics data was then used to build models distinguishing between NAFLD and cirrhosis.

The findings thus offer a route for creating non-invasive technologies to assess and diagnose NAFLD.

The pleiotropic effects of the discovered variations were also investigated by examining relationships with 52 additional phenotypes and attributes.

BMI is one of the most prevalent risk factors for NAFLD, and longitudinal PDFF measurements revealed that carriers of the well-known NAFLD risk variation p.Ile148Met in PNPLA3 are more vulnerable to change in BMI than non-carriers.

This study is among the largest ones on the genetic basis of NAFLD to date, and the findings should help create diagnostic procedures and treatments for NAFLD patients.

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