Clinical, Biochemical and Body Composition Analysis in Assessment of Steatosis in Non Alcoholic Fatty Liver Disease

Non-alcoholic fatty liver disease (NAFLD) includes a spectrum of liver disorders characterized by accumulation of hepatic fat in absence of significant alcohol consumption (\<20 gm/day) and other causes of liver diseases. It is the most common cause of asymptomatic elevation of liver enzymes worldwide (Marchesini et al., 2003). Unfortunately, to date, existing non- or minimally invasive biomarkers are inadequate. While a number of non- or minimally invasive tests are able to rule out fibrosis or cirrhosis, no single test to identify steatosis, to early diagnose NASH, or to predict the disease progression is available. Moreover, specialized, combined tests are required to assess treatment response in clinical trials on emerging compounds (Piazzolla and Mangia, 2020). Among minimally invasive tools, plasma biomarkers and composite scores defined as "wet biomarkers" are commonly used. For example, fasting insulin level and its use in measurement of insulin resistance, Lipid Accumulation Product (LAP) score (Bedogni et al., 2010), the NAFLD Liver Fat Score (NLFS) (Kontronen et al., 2009), Hepatic Steatosis Index (HSI) (Lee et al., 2010), controlled attenuation parameter (CAP) measurement by fibroscan (Piazzolla and Mangia, 2020). Recent studies have shown that CAP significantly correlates with the percentage of steatosis and steatosis grade and that median CAP is higher among patients with significant steatosis (Sasso et al., 2012 \& Karlas et al., 2017). The prevalence of NAFLD is 80-90% in obese, 30-50% in patients with diabetes and up to 90% in patients with hyperlipidemia (Abenavoli et al., 2014) Central obesity or visceral fat (VF) (determined by waist circumference (WC)) is defined as the presence of excess fat in the abdomen, and this type of obesity is often associated with the development and progression of NAFLD or more advanced forms of liver disease (Abenavoli et al., 2016). Thus, measurement of body composition rather than BMI may be helpful in the predict