Clinical Trial Details
— Status: Recruiting
Administrative data
| NCT number |
NCT06098417 |
| Other study ID # |
NALFD biomarkers |
| Secondary ID |
|
| Status |
Recruiting |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
September 22, 2015 |
| Est. completion date |
September 22, 2026 |
Study information
| Verified date |
October 2023 |
| Source |
University of Trieste |
| Contact |
Silvia Palmisano, MD |
| Phone |
0403994152 |
| Email |
spalmisano[@]units.it |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational
|
Clinical Trial Summary
Fibrosis is considered the leading cause of liver diseases and related mortality.
Specifically, hepatic fibrosis is regarded as the consequence of reparative mechanisms
initiated by hepatocytes in response to chronic damage. In Western countries, the main known
etiologies include hepatitis (B and C), alcoholism, and non-alcoholic steatohepatitis (NASH).
In particular, obesity is a determining factor in the onset and development of NASH. Alarming
statistical data indicate that over 30% of the world's population is obese, and this eating
disorder is increasingly affecting young people. NASH is a chronic disease that can present
different degrees of fibrosis and, as the final stage, lead to the development of liver
cirrhosis. Currently, the only accurate diagnostic and assessment system for this condition
is liver biopsy, as there are no accurate non-invasive clinical tests available. The aim of
this project is to identify (in silico) potential biomarkers involved in the development and
progression of hepatic fibrosis and validate their presence and quantity in serum or plasma
samples from obese patients (at-risk population). This would avoid the need for a liver
biopsy and allow "at-risk" patients to undergo a simple ambulatory blood draw. Additionally,
performing elastometry of the liver would allow for comparison of radiological results with
laboratory findings.
Description:
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.
