Исследование Майо Клиник выявило пять биологически различных подтипов жирового гепатоза

A liver disease affecting nearly 30% of adults worldwide is not a single illness but five biologically distinct subtypes, Mayo Clinic researchers have found. Each carries different risks for heart disease, liver failure, cancer and the need for liver transplantation. The study, published in Nature Communications and conducted in collaboration with scientists at Virginia Tech, shows that metabolic dysfunction-associated steatotic liver disease has multiple pathways - some tied to obesity and diabetes, others driven by inherited genetic factors. Notably, genetic subtypes are associated with a higher risk of progression to advanced liver disease, including in patients without typical metabolic risk factors. The findings could help identify high-risk patients earlier and guide more precise screening and personalized treatment. "When clinical and genomic data are analyzed together at this scale, you begin to see patterns of disease progression that would otherwise remain hidden," says Shulan Tian, Ph.D., co-senior author and a bioinformatician at Mayo Clinic. "Once you separate these subtypes, you can start to match treatments to the biology that's actually driving the disease." Metabolic dysfunction-associated steatotic liver disease, formerly called nonalcoholic fatty liver disease, occurs when fat builds up in the liver. It often develops without symptoms but can progress to inflammation, scarring and irreversible damage. It is a leading cause of cirrhosis, liver cancer and transplantation worldwide. Decoding liver disease at scale To uncover these subtypes, researchers integrated genetic sequencing with detailed clinical data from more than 4,600 patients with the disease. The dataset spanned a wide range of measures - from liver enzymes, body mass index and lipid levels to coexisting conditions such as diabetes, depression and sleep apnea. Using advanced computational modeling, the team identified groups of patients who shared underlying biological signals, defining distinct subtypes of the disease. "What's emerging here is a way to systematically identify meaningful subgroups within complex disease," says Eric Klee, Ph.D., co-senior author and the Everett J. and Jane M. Hauck Midwest Associate Director of Research and Innovation. "It helps us map complex disease with such precision that we can begin to anticipate its course and intervene before the most serious damage occurs." The discovery was powered by Mayo Clinic's Research Data Atlas, a platform that connects genetic data with patient records to reveal patterns across large populations - a system Dr. Klee helped build. A key component of the Atlas is the Tapestry Study, which has generated Mayo Clinic's largest collection of exome data from more than 100,000 participants. The dataset captures key genetic information that shapes how diseases develop and progress. "This is exactly the kind of insight large-scale genomic research was built to deliver," says Konstantinos Lazaridis, M.D., the Carlson and Nelson Endowed Executive Director for the Center for Individualized Medicine who led the Tapestry Study and is a co-author of the research. "When you connect genetic data with detailed clinical information across large populations, you can start to redefine diseases in ways that directly impact patient care." Liver disease's hidden effects across the body The study also revealed links beyond the liver. For the first time, researchers found that specific subtypes are associated with conditions such as depression, sleep apnea and migraine, underscoring the disease's broad systemic impact across multiple organ systems. Next, the team plans to test the approach in broader patient populations and explore how these subtypes respond to different treatments, including therapies such as GLP-1 receptor agonists. First author Tahmina Sultana Priya, now a Ph.D. student at Virginia Tech, contributed to the research while at Mayo Clinic. For a complete list of authors, disclosures and funding, review the study.