Biomarkers in the Diagnosis and Prognosis of NAFLD

Project Description: In modern society, with the advent of industrial development, lifestyle has been greatly modified, leading to unhealthy habits such as overeating and fast food consumption (following an unbalanced diet rich in sugars and fats) and reduced physical activity. In the European Union, over half of adults are overweight or obese. This group of individuals is considered at high risk for the development of chronic liver diseases such as non-alcoholic fatty liver disease (NAFLD). Many epidemiological reports have linked the onset of NAFLD to poor dietary choices and sedentary habits. Currently, there are no effective pharmacological therapies, and the only way to prevent or improve the condition is by leading a healthier lifestyle (personalized diets, physical activity, and cognitive-behavioral psychological therapies). The main limitation to this solution is the lack of patient adaptability to the therapy. NAFLD encompasses a wide histological spectrum ranging from simple steatosis to non-alcoholic steatohepatitis (NASH). NASH is characterized by steatosis with inflammation and can present different stages of fibrosis, from absent to cirrhosis. The gold standard for diagnosis and evaluation of fibrosis stage remains liver biopsy. However, performing a liver biopsy for every suspected NAFLD patient is impossible, both for ethical reasons and because it is not a valid screening method. Therefore, it is necessary to develop non-invasive methods for screening and diagnosis. Furthermore, early diagnosis could increase patient awareness of their chronic disease and motivate them to change their lifestyle. Considering this, it is therefore necessary to develop non-invasive methods for screening and diagnosis. Furthermore, early diagnosis could increase the patient's awareness of their chronic condition and convince them to change their lifestyle. It should be considered that identifying new markers can be a very challenging task due to: Complexity of physiopathology. Multiple factors involved in disease progression. Presence of common mediators in many other fibrotic disorders. Therefore, an original strategy aimed at discovering new biomarkers is of fundamental importance. Thanks to the development of high-throughput technologies, nowadays a huge amount of genomic and proteomic data is easily accessible in online databases. It is thus possible to study the interactome (protein-protein interactions -PPI- within a cell) using open-source software such as Cytoscape. In this way, the use of bioinformatics allows us to analyze in silico biological network data, which represents a way to identify biomarkers of clinical interest without the need for expensive equipment. Objective: The aim of this project is to identify (through in silico analysis) and validate new biomarkers that are useful for the diagnosis and prognosis of NAFLD, which can be used in non-invasive clinical tests. Our initial approach in identifying candidate biomarkers was to use the following working criteria in in silico studies: 1. Obtain PPI data from databases that adhere to the guidelines of the International Molecular Exchange (IMEx) consortium. 2. Construct biological networks for the proteins listed in Table 1 (which have been proposed as candidates for the diagnosis of NAFLD in recent scientific journals). 3. Construct biological networks for proteins released by hepatic stellate cells (HSCs) that indicate activation/reversion of the myofibroblastic phenotype (HSCs are the main cells involved in liver fibrosis). See Table 1. 4. Include in our studies the known marker of HSC activation (α-smooth muscle actin, α-SMA) and an essential component of the extracellular matrix (ECM): collagen alpha-III type I (Col3A1). 5. Choose proteins of interest, i.e., those that are released in the serum and that connect the largest number of biological networks. Table 1 - Candidate biomarkers described in the literature Protein Relevant information Localization Cytokeratin-18 (CK-18) Indicator of hepatocellular apoptosis. Proposed as a biomarker in NAFLD Cytoplasm, nucleus Adipocyte fatty acid binding protein (AFABP) Reported as a biomarker in NAFLD Cytoplasm Fibroblast growth factor 21 (FGF21) Increased expression in the liver and serum, correlated with the degree of steatosis Released Insulin-like growth factor-binding protein 3 (IGFBP-3) Proposed as a biomarker for NAFLD in a recent serum proteome study Secreted Lymphocyte cytosolic protein 1 (LCP1) Actin-binding protein, suggested as a biomarker in NAFLD Cytoplasm, membrane Galectin-1 (LGALS1) Increased expression in activated HSCs Secreted Ubiquitin conjugation factor E4B (UBE4B) Increased expression in activated HSCs Cytoplasm, secreted Vitronectin (VTN) Increased expression in inactivated HSCs Secreted Osteopontin (OPN) Component of the ECM Secreted Laminin subunit beta 1 (LAMB1) Reduced expression in inactivated HSCs Secreted α-SMA Increased expression in activated HSCs Cytoplasm Col3A1 Increased production in fibrogenesis (component of the extracellular matrix) Secreted Based on the described working criteria and using Cytoscape, we obtained an integrated biological network (Figure 1), where each of the PPI networks created for the proteins in Table 1 (12 biological networks) was connected through common interaction proteins (common partners). These common proteins, especially those released by cells (soluble factors), will be our target proteins. From our preliminary analysis, we have identified the following proteins as potential biomarkers: IGF-2 (insulin-like growth factor 2), SPARC (secreted protein acidic and rich in cysteine), EPICAN, and EGFR (epidermal growth factor receptor) (highlighted in red in Figure 1). Experimental Plan The research activities will be conducted at the Italian Liver Foundation. The sample collection will take place at the General Surgery Department of Cattinara Hospital. To achieve the described objectives, groups of patients candidates for bariatric surgery at the General Surgery Unit will be involved. A medical visit is scheduled, during which general clinical information will be collected, and measurements of weight, height, waist circumference, and blood pressure will be taken. As part of the routine pre-surgery preparations and outpatient follow-up, general hematological and biochemical parameters (complete blood count, glucose, insulin, triglycerides, total cholesterol, HDL, transferrin, ferritin, serum iron, C-reactive protein), liver function (transaminases, albumin, total protein), and kidney function (creatinine, urinary creatinine, microalbuminuria) will be evaluated through common laboratory tests on plasma/serum samples. An additional aliquot of the collected samples will be used for RNA and protein extraction and subsequent assessment of sample quality. Undergoing a blood draw, which is routinely performed for diagnostic investigations and preoperative assessment, may involve momentary pain at the puncture site and the appearance of a bruise (hematoma), complications that can occur with any blood collection. Furthermore, before the surgery, liver elastometry will be performed, which will allow us to compare the radiological results with the laboratory results. This is a non-invasive examination similar to an ultrasound. These investigations will be repeated after one year following the surgery to quantify the expected improvements, while only the blood draw will be repeated after six months. Both procedures will be covered by the General Surgery Department. During the bariatric surgery, which is scheduled for obesity according to the national guidelines of SICOB, subcutaneous, liver, and visceral fat biopsies will be performed. These biopsies do not significantly prolong the surgical times. In these three samples, the presence and quantity of the studied markers will be verified. Additionally, a portion of the liver biopsy will be sent to the pathology department for definitive histological examination to study the degree of fibrosis and steatosis. The collected and preserved samples for this research will be used to monitor the patient's health status. Furthermore, the results of this study could be helpful to other patients by contributing to the improvement of the treatment and prevention of non-alcoholic fatty liver disease. The patient scheduled for the surgery will be given and explained an informed consent form prior to the procedure, where the aforementioned procedures, risks, and benefits are described. The experimental plan can be divided into three phases: Phase 1: In-depth in silico studies. Estimated time: 1 month. Phase 2: In vivo studies, sample collection (blood and liver), sample bank. Collection of clinical and laboratory data for each patient. Extraction of RNA and proteins, followed by the evaluation of sample quality. Quantification of mRNA expression for the panel of biomarkers (Table 1 + potential biomarkers). Serum and tissue (liver) quantification of candidate biomarkers using ELISA/Western blot. Estimated time: 9 months. Phase 3: Validation of results: The obtained results will be correlated with clinical-analytical data (blood values), liver biopsy data (histopathological data), and available imaging techniques (ultrasound, elastography) at Cattinara Hospital. Statistical analysis will be performed to correlate the new biomarkers with the stage of the disease. Estimated time: 2 months. Figure 1: In silico studies. Sample size and statistical analysis: The enrollment of a total of 62 patients, both inpatients and outpatients, is planned for the study. The fundamental equation for calculating the sample size is as follows: N = (2 x (Zα + Zβ)2 x S2) / d2 N = required subjects in each sample group. We established two groups: Group A (without or with mild fibrosis, Brunt: 0-1) and Group B (moderate to severe fibrosis, Brunt: 2-3). Zα = Z-value for the desired risk (for us, it is 1.96 for a bilateral test). Zβ = Z-value for the desired risk (for us, it is 1.282 for a bilateral test). S2 = Variance or dispersion of the quantitative parameter for the control or reference group (for us, reference group: Group A, dispersion value = 150 U/L). d = Minimum value of the detectable difference (for us, 200 U/L). The calculated sample size for each group using this procedure is 29.3. Adding a correction for the possibility of sample loss at 5% yields a total of 30.87. The total number of samples is 62. We applied this analysis to one of the markers in the study (CK-18) because it is the most reported in the literature. Since our study involves the study of 4 biomarkers, it is possible that working with a panel of markers will increase the likelihood of study outcomes (potentially reducing the required number of samples). Utility of the study: In the field of chronic liver diseases such as NAFLD, there is an urgent need for the identification and development of non-invasive techniques for diagnosis and clinical prognosis. These methods will lead to faster clinical decision-making, benefiting both patients and medical staff. Therefore, the results obtained from this study aim to contribute to the identification and validation of new serum biomarkers to improve the diagnosis, screening, and treatment of NAFLD. Furthermore, it is hoped that the validated biomarkers can also be used as prognostic markers in other liver diseases that progress with inflammation and fibrosis. The availability of non-invasive biomarkers would have an immediate impact in clinical practice, distinguishing between individuals with a high fibrosis progression rate and those who may remain in a non-proliferative phase or even achieve remission. This information would contribute to a more accurate selection and efficacy of therapy, thereby improving the overall patient outcome. Additionally, the identification of specific biomarkers, along with the presence of a biological sample bank in our institution, provides the potential to thoroughly study the molecular processes involved not only in this condition but also in other fibrogenic processes in the liver, with the possibility of identifying new pharmacological targets. Given the observational nature of the proposed study, no additional insurance policies are required beyond those already provided for normal clinical practice.