A tool to predict progression of non-alcoholic fatty liver disease in severely obese patients

A Model-Based Evaluation of Noninvasive Biomarkers to Reflect Histological Nonalcoholic Fatty Liver Disease Scores

BACKGROUND

Nonalcoholic fatty liver disease (NAFLD) comprises multiple heterogeneous pathophysiological conditions commonly evaluated by suboptimal liver biopsies. This study aimed to elucidate the role of 13 diverse histological liver scores in assessing NAFLD disease activity using an in silico pharmacometric model-based approach. We further sought to investigate various noninvasive patient characteristics for their ability to reflect all 13 histological scores and the NAFLD activity score (NAS).

METHODS

A histological liver score model was built upon 13 biopsy-based pathological features (binary and categorical scores) from the extensive NASH-CRN (Nonalcoholic Steatohepatitis-Clinical Research Network) observational NAFLD Database study (n = 914 adults) using the concept of item response theory. The impact of 69 noninvasive biomarkers potentially reflecting NAFLD activity was quantitatively described across the entire spectrum of all 13 histological scores.

RESULTS

The model suggested that four different disease facets underlie the cardinal NAFLD features (steatosis, inflammation, hepatocellular ballooning (= NAS); fibrosis; highest correlations: corrballooning-fibrosis = 0.69/corrinflammation-ballooning = 0.62/corrsteatosis-inflammation = 0.60). The 13 histological liver scores were best described by contrasting noninvasive biomarkers: Age and platelets best reflected the fibrosis score, while alanine and aspartate aminotransferase best described the NAS, with diverging contributions of the three individual NAS components to the results of the overall NAS.

CONCLUSIONS

An in silico histological liver score model allowed to simultaneously quantitatively analyze 13 features beyond NAS and fibrosis, characterizing different disease facets underlying NAFLD and revealing the contrasting ability of 69 noninvasive biomarkers to reflect the diverse histological (sub-)scores.

Early prediction of the impact of public health policies on obesity and lifetime risk of type 2 diabetes: A modelling approach

OBJECTIVE

Help public health decision-making requires a better understanding of the dynamics of obesity and type 2 diabetes and an assessement of different strategies to decrease their burdens.

METHODS

Based on 97,848 individual data, collected in the French Health, Health Care and Insurance Survey over 1998-2014, a Markov model was developed to describe the progression of being overweight to obesity, and the onset of type 2 diabetes. This model traces and predicts 2022-2027 burdens of obesity and type 2 diabetes, and lifetime risk of diabetes, according to different scenarios aiming at minimum to stabilize obesity at 5 years.

RESULTS

Estimated risks of type 2 diabetes increase from 0.09% (normal weight) to 1.56% (obesity II-III). Compared to the before 1995 period, progression risks are estimated to have nearly doubled for obesity and tripled for type 2 diabetes. Consequently, over 2022-2027, the prevalence of obesity and type 2 diabetes will continue to increase from 17.3% to 18.2% and from 7.3% to 8.1%, respectively. Scenarios statibilizing obesity would require a 22%-decrease in the probability of move up (scenario 1) or a 33%-increase in the probability of move down (scenario 2) one BMI class. However, this stabilization will not affect the increase of diabetes prevalence whereas lifetime risk of diabetes would decrease (30.9% to 27.0%). Combining both scenarios would decrease obesity by 9.9%. Only the prevalence of obesity III shows early change able to predict the outcome of a strategy: for example, 6.7%-decrease at one year, 13.3%-decrease at two years with scenario 1 stabilizing obesity at 5 years.

CONCLUSIONS

Prevalences of obesity and type 2 diabetes will still increase over the next 5 years. Stabilizing obesity may decrease lifetime risks of type 2 diabetes without affecting its short-term prevalence. Our study highlights that, to early assess the effectiveness of their program, public health policy makers should rely on the change in prevalence of obesity III.

Recent Progresses on Pathophysiology, Diagnosis, Therapeutic Modalities, and Management of Non-alcoholic Fatty Liver Disorder

Abstract:

Non-alcoholic fatty liver disease (NAFLD) is currently the utmost common chronic liver disorder that happens through all age groups and is identified to occur in 14%-30% of the general population, demonstrating a critical and grossing clinical issue because of the growing incidence of obesity and overweight. From the histological aspect, it looks like alcoholic liver damage, but it happens in patients who avoid remarkable alcohol usage. NAFLD comprises a broad spectrum, ranging from benign hepatocellular steatosis to inflammatory nonalcoholic steatohepatitis (NASH), different levels of fibrosis, and cirrhosis. Patients with NASH are more susceptible to more rapid progression to cirrhosis and hepatocellular carcinoma. There is no single factor that drives proceeding from simple steatosis to NASH. However, a combination of multi parameters such as genetic background, gut microflora, intake of high fat/ fructose dietary contents or methionine/choline-deficient diet, and consequently accumulated hepatocellular lipids mainly including triglycerides and also other bio-analytes, such as free fatty acids, cholesterol, and phospholipids display a crucial role in disease promotion. NAFLD is related to overweight and insulin resistance (IR) and is regarded as the hepatic presentation of the metabolic syndrome, an amalgamation of medical statuses such as hyperlipidemia, hypertension, type 2 diabetes, and visceral obesity. Despite the increasing prevalence of this disease, which imposes a remarkable clinical burden, most affected patients remain undiagnosed in a timely manner, largely related to the asymptomatic entity of NAFLD patients and the unavailability of accurate and efficient noninvasive diagnostic tests. However, liver biopsy is considered a gold standard for NAFLD diagnosis, but due to being expensive and invasiveness is inappropriate for periodic disease screening. Some noninvasive monitoring approaches have been established recently for NAFLD assessment. In addition to the problem of correct disease course prediction, no effective therapeutic modalities are approved for disease treatment. Imaging techniques can commonly validate the screening and discrimination of NAFLD; nevertheless, staging the disease needs a liver biopsy. The present therapeutic approaches depend on weight loss, sports activities, and dietary modifications, although different insulin-sensitizing drugs, antioxidants, and therapeutic agents seem hopeful. This review aims to focus on the current knowledge concerning epidemiology, pathogenesis, and different biochemical experiments and imaging modalities applied to diagnose the different grades of NAFLD and its management, as well as new data about pharmacological therapies for this disorder.

Biomarkers of Metabolic (Dysfunction)-associated Fatty Liver Disease: An Update

The prevalence of metabolic (dysfunction)-associated fatty liver disease (MAFLD) is rapidly increasing and affects up to two billion individuals globally, and this has also resulted in increased risks for cirrhosis, hepatocellular carcinoma, and liver transplants. In addition, it has also been linked to extrahepatic consequences, such as cardiovascular disease, diabetes, and various types of cancers. However, only a small proportion of patients with MAFLD develop these complications. Therefore, the identification of high-risk patients is paramount. Liver fibrosis is the major determinant in developing these complications. Although, liver biopsy is still considered the gold standard for the assessment of patients with MAFLD. Because of its invasive nature, among many other limitations, the search for noninvasive biomarkers for MAFLD remains an area of intensive research. In this review, we provide an update on the current and future biomarkers of MAFLD, including a discussion of the associated genetics, epigenetics, microbiota, and metabolomics. We also touch on the next wave of multiomic-based biomarkers.