DOI 10.1080/17474124.2023.2191190
Advances in our understanding of the molecular heterogeneity of fatty liver disease: toward informed treatment decision making.
Аннотация
INTRODUCTION
nonalcoholic fatty liver disease (NAFLD) is a complex disorder resulting from intricate relationships with diverse cardiometabolic risk factors and environmental factors. NAFLD may result in severe chronic liver damage and potentially declining liver function.
AREAS COVERED: Accumulated knowledge over the last decade indicates that the disease trajectory presents substantial heterogeneity. In addition, overlapping features with the diseases of the metabolic syndrome, combined with heterogeneity in disease mechanisms, further complicates NAFLD diagnosis and prognosis, and hampers progress in biomarker and pharmacological discoveries. Here, we explore solving the heterogeneous clinical landscape of NAFLD by cluster analysis of molecular signatures that serve as a proxy for disease stratification into molecular sub-types. First, we collected information on NAFLD and metabolic syndrome-associated protein-coding genes by data mining the literature. Next, we performed pathways enrichment and cluster analyses to decipher and dissect the different patterns of phenotypic heterogeneity. Our approach showed unique biological pathways for every clinical subtype/group, namely NAFLD + obesity, NAFLD + arterial hypertension, NAFLD + dyslipidemia, and NAFLD + type 2 diabetes.
EXPERT OPINION: Patients with NAFLD may be benefited by a better understanding of the disease biology, which involves 'dissection' of the molecular sub-phenotypes that drive the disease progression.
Предметные рубрики MeSH
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.