Non-Invasive MASLD Diagnosis & T2D Remission Biomarkers

To assess the diagnostic accuracy of three ultrasonography tools for diagnosing MASLD by calculating their sensitivity (%), specificity(%), positive predictive value (PPV)(%), and negative predictive value (NPV)(%) compared to the liver histopathology diagnosis:

• Conventional Ultrasonography: Detects liver steatosis and evaluates liver size (cm), texture, and fibrosis.
• Shear-wave elastography (SWE): Measures liver stiffness(kPa), correlating with fibrosis severity (F0-F1: 0.0 - 8.27 kPa = Normal-mild, F2: 8.27 - 9.4 kPa = mild-moderate, F3: 9.4-11.8 kPa = moderate-severe, F4: >11.8 kPa cirrhosis).
• Ultrasound-guided acoustic pulse (UGAP) examination: Combines ultrasound with acoustic pulses to assess liver steatosis by measuring the attenuation of ultrasound waves as they pass through the liver. Higher attenuation values generally correlate with a greater degree of hepatic steatosis (attenuation coefficient cutoff value (dB/cm/MHz): ≥S1= 0.65, ≥S2= 0.71, S3= 0.77).

This outcome measures changes in protein expression between MASLD-positive patients and a control of MASLD- negative patients. Both group will have equal number of participants, and equal male to female ratio.

Protein levels will be measured using liquid chromatography tandem mass spectrometry (counts per second (cps), and Changes in protein levels and will be quantified as percent and fold changes.

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To evaluate the diagnostic accuracy of three formulae for diagnosing MASLD by assessing Sensitivity(percentage), Specificity(percentage), Positive Predictive Value (PPV)(percentage), and Negative Predictive Value (NPV)(percentage) compared to the liver histopathology diagnosis.

• APRI: Uses AST levels (U/L) and platelet count (x10^9/l) to estimate liver fibrosis risk (< 0.5 = minimal or no fibrosis, 0.5 - 1.5 = Moderate fibrosis, > 1.5 = Severe fibrosis or cirrhosis).
• FIB-4: Combines age(years), AST(U/L), ALT(U/L), and platelet count (x10^9/l) to assess liver fibrosis risk (< 1.45 = minimal or no fibrosis, 1.45 - 3.39 = significant fibrosis, ≥ 3.4 = advanced fibrosis or cirrhosis).
• NAFLD-Fibrosis Score: Uses age (years), BMI (kg/m^2), diabetes status, liver enzymes (U/l), platelet count (x10^9/l), and albumin (g/L) to assess fibrosis risk (< -1.455 = low probability of fibrosis, -1.455- 0.765 = significant fibrosis, > 0.675 = high probability of fibrosis).

This outcome measures changes in circulating microRNA (miRNA) levels, in relation to diabetes remission post-bariatric surgery. Changes in miRNA levels will be quantified as percent and fold changes.

miRNA levels will be measured using micro-array technique. Changes will be assessed in the diabetic disease state and after achieving diabetes remission, defined by fasting glucose <100 mg/dL and HbA1c <6.5%.

miRNA changes will be correlated with diabetes remission at 6 and 12 months.

This outcome aims to assess the regression of Metabolic Dysfunction-associated Steatotic Liver Disease (MASLD) after bariatric surgery. MASLD regression will be evaluated through changes in liver stiffness, liver enzymes, inflammatory markers, and MASLD risk scores:

• Liver Stiffness (kPa): Measured by elastography. A decrease of at least 30% from baseline suggests regression.
• Liver Enzymes [AST, ALT, ALP, GGT (U/L)]: A significant decrease in enzyme levels indicates improved liver function.
• Inflammatory Markers: A reduction in inflammatory markers (e.g., CRP) signals MASLD improvement.
• MASLD Risk Scores:

• FIB-4: A reduction in score suggests decreased fibrosis.
• APRI: A decrease indicates improved liver function.
• NAFLD-Fibrosis Score: A reduction suggests MASLD regression.

MASLD regression will be assessed at 6- and 12-months post-surgery, focusing on these markers and risk scores.

This outcome evaluates the remission of Type 2 Diabetes Mellitus (T2DM) following bariatric surgery. T2DM remission will be determined by changes in fasting glucose and glycated hemoglobin (HbA1c) levels:

Fasting Glucose: Fasting glucose levels will be measured after an overnight fast. A fasting glucose level below 100 mg/dL will be considered indicative of T2DM remission.

Glycated Hemoglobin (HbA1c): HbA1c levels reflect average blood glucose over the past 2-3 months. T2DM remission is defined as an HbA1c level below 6.5% without the need for diabetes medications.

T2DM remission will be assessed at 6 and 12 months following bariatric surgery, with remission defined by meeting the aforementioned glucose and HbA1c thresholds.

This outcome assesses the effectiveness of bariatric surgery in terms of Excess Weight Loss (EWL). EWL will be calculated based on individual measurements of weight and ideal body weight.

• Pre-surgery Weight (kg): Weight will be measured before surgery.
• Post-surgery Weight (kg): Weight will be measured at 6 and 12 months.
• Ideal Body Weight (kg): Ideal body weight (IBW) will be calculated using one of the following formulae based on patients' gender:

For Men:

IBW (kg) = 50 + 0.91 × (height in cm - 152.4)

For Women:

IBW (kg) = 45.5 + 0.91 × (height in cm - 152.4)

• Excess Weight Loss (EWL): EWL will be calculated as:

EWL (%) = [(Pre-surgery weight - Ideal body weight) / (Pre-surgery weight - post-surgery weight)] × 100

• Statistical Analysis: Paired t-tests will compare pre- and post-surgery weight. Regression models will assess factors affecting EWL and its link to clinical outcomes.

The body composition is measured using Bioelectrical Impedance Analysis (BIA) device to assess the proportions of fat, muscle, bone, and water in the body.

The following parameters are measured at baseline, and then at 6 and 12 months after bariatric surgery: Weight (kg), Height (m),BMI (kg/m^2), Fat Mass (kg), Fat Free Mass (kg), Fat Percentage (%), Bone Mass (kg), Muscle Mass (kg), Total Body Water (kg), Intracellular Water (kg), Extracellular water (kg), Visceral Fat Rating, Metabolic age (years)

All parameters are measured using a fully-automated BIA scales.

This outcome measures the identification of novel biomarkers, proteins and microRNAs, through fold change analysis and regression models. Fold change analysis compares biomarker expression between groups (e.g., patients vs. controls or pre-treatment vs. post-treatment), with a threshold of a 1.5-fold change indicating significant differences. Regression models assess the relationship between biomarker levels and clinical factors (e.g., disease progression, treatment response). Biomarker expression was measured using molecular techniques, namelymicro-arrays and tandem mass spectrometry. The goal is to identify biomarkers that could aid in disease diagnosis, prognosis, or treatment monitoring, providing a foundation for personalized medicine.