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| ID | Type | Description | Link |
|---|---|---|---|
| RMS-KHUH /IRB/ 2024-788 | Other Identifier | Bahrain Defence Force - Royal Medical Services |
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| Name | Class |
|---|---|
| King Hamad University Hospital, Bahrain | OTHER |
| King Faisal Specialist Hospital & Research Center | OTHER |
| King Fahad Medical City | OTHER_GOV |
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The goal of this observational study is to prospectively develop and validate a non-invasive scoring system based on metabolic markers, proteomic, and transcriptomic profiles to accurately screen, diagnose, stage, and monitor Metabolic dysfunction-associated steatotic liver disease (MASLD) activity and regression as a replacement for the invasive liver biopsy tool in Bahraini bariatric patients. The study also aims to identify biomarkers for predicting type 2 diabetes mellitus remission post-bariatric surgery. The main questions it aims to answer are:
Participants will undergo comprehensive assessments, including anthropometric measurements, metabolic biomarker evaluations, proteomic, and transcriptomic profiling at three time points: before surgery, and at 6- and 12-months post-surgery. The data collected will inform the development of the non-invasive scoring system, which will be tested for its reliability and accuracy in replacing liver biopsy as the standard diagnostic tool for MASLD.
Metabolic dysfunction Associated Steatotic Liver Disease (MASLD), previously known as NonAlcoholic Fatty Liver Disease (NAFLD), is becoming the most common cause of liver disease in adults with the pandemic of obesity in this century. MASLD is affecting more than quarter of the whole population on earth and the highest prevalence is in the middle east region. A recent retrospective study performed on bariatric patients at the King Hamad University Hospital (KHUH) reported a prevalence of 82.3% of MASLD before the surgery. MASLD progression may lead to liver cirrhosis following which the liver cells become damaged irreversibly. The current gold standard to diagnose MASLD is liver biopsy, however, this method has several limitations due to its invasive nature.
This observational study aims to study MASLD in depth utilizing molecular analysis tools, which can yield more information about disease progression in bariatric patients specific to the Bahraini population.
The total sample size of our study is estimated to be around 163 participants of which 134 subjects would to be positive cases of MASLD. We will include the patients undergoing bariatric surgery from the January to December 2025. An informed consent will be taken from the patients to participate in the research while consenting them for the surgery. The surgeon will inform the participant that radiological and biochemical investigations will be done pre-operatively as well as wedge liver biopsy will be taken during the laparoscopic procedure.
Several data will be collected from the enrolled patients' medical records to study disease progression before the surgery, 6 months and 12 months after the surgery:
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| MASLD metabolic biomarker | Adult obese patients (18 years old and above) who underwent bariatric surgery in KHUH surgery department from January 2025 to December2025. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Bariatric Surgery | Procedure | A surgical procedure used to manage obesity and obesity-related conditions. |
|
| Measure | Description | Time Frame |
|---|---|---|
| Accuracy of Non-invasive Ultrasonography Tools for MASLD Assessment | 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:
| At Baseline, at 6-months after the surgery, and at 12 months after the surgery |
| Proteomic Changes and Their Correlation with MASLD Regression | 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. . | At Baseline |
| Accuracy of Available Formulae for MASLD Assessment | 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.
|
| Measure | Description | Time Frame |
|---|---|---|
| Percentage of MASLD Regression Post-Bariatric Surgery | 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:
MASLD regression will be assessed at 6- and 12-months post-surgery, focusing on these markers and risk scores. |
| Measure | Description | Time Frame |
|---|---|---|
| Identification of Novel Biomarkers through Fold Change Analysis and Regression Models | 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. |
Inclusion Criteria:
Exclusion Criteria:
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Bahraini adult obese patients
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| Name | Affiliation | Role |
|---|---|---|
| John Flood | RCSI-MUB | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Alhakeem Radiology Center | Manama | Manama | 2901 | Bahrain | ||
| King Hamad University Hospital |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 27891446 | Background | Bujang MA, Adnan TH. Requirements for Minimum Sample Size for Sensitivity and Specificity Analysis. J Clin Diagn Res. 2016 Oct;10(10):YE01-YE06. doi: 10.7860/JCDR/2016/18129.8744. Epub 2016 Oct 1. | |
| 35191926 | Background | Slomski A. Bariatric Surgery Approaches Reduce Fatty Liver Disease. JAMA. 2022 Feb 22;327(8):710. doi: 10.1001/jama.2022.1532. No abstract available. |
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Monitoring, audits, and REC review will be permitted and provide direct access to source data and documents. The Lead PI and the researchers assigned by him will have access to the stored data/specimens. Only the Lead PI and the researchers assigned working on this study will be eligible to obtain the data/specimens from the participants during data collection.
Data will be collected in the case report form to allow for cross referencing to check validity.
Study documents (paper) will be retained in a secure (kept locked when not in use) location during and after the trial has finished. All essential documents including source documents will be retained for a period of 5 years after study completion (last patient, last study point).
Study documents (paper) will be retained in a secure (kept locked when not in use) location during and after the trial has finished.
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| ID | Term |
|---|---|
| D003924 | Diabetes Mellitus, Type 2 |
| D065626 | Non-alcoholic Fatty Liver Disease |
| D009765 | Obesity |
| ID | Term |
|---|---|
| D003920 | Diabetes Mellitus |
| D044882 | Glucose Metabolism Disorders |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
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| ID | Term |
|---|---|
| D050110 | Bariatric Surgery |
| D000713 | Anastomosis, Roux-en-Y |
| D015904 | Biliopancreatic Diversion |
| D015390 | Gastric Bypass |
| ID | Term |
|---|---|
| D049088 | Bariatrics |
| D000073319 | Obesity Management |
| D013812 | Therapeutics |
| D013514 | Surgical Procedures, Operative |
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5 ml of centrifuged serum blood sample will be retained. liver biopsy sample
| At Baseline, at 6-months after the surgery, and at 12 months after the surgery |
| mi-RNA Changes and Their Correlation with MASLD Regression and Diabetes Remission | 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. | At Baseline, at 6-months after the surgery, and at 12 months after the surgery |
| At 6-months after the surgery, and at 12 months after the surgery |
| Percentage of Type 2 Diabetes Remission Post-Bariatric Surgery | 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. | At 6-months after the surgery, and at 12 months after the surgery |
| Excess Weight Loss (EWL) Measurement | 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.
| At Baseline, at 6-months after the surgery, and at 12 months after the surgery |
| Body Composition Parameters After Bariatric Surgery | 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. | At baseline, and at 6 months and 12 months after bariatric surgery |
| Through study completion, an average of 1 year |
| Al Muharraq |
| Muharraq |
| Bahrain |
| 37666725 | Background | Poljo A, Kopf S, Sulaj A, Roessler S, Albrecht T, Goeppert B, Bojko S, Muller-Stich BP, Billeter AT. The role of bariatric surgery on beta-cell function and insulin resistance in patients with nonalcoholic fatty liver disease and steatohepatitis. Surg Obes Relat Dis. 2023 Dec;19(12):1421-1434. doi: 10.1016/j.soard.2023.07.005. Epub 2023 Jul 24. |
| 36545709 | Background | Geerts A, Lefere S. Bariatric surgery for non-alcoholic fatty liver disease: Indications and post-operative management. Clin Mol Hepatol. 2023 Feb;29(Suppl):S276-S285. doi: 10.3350/cmh.2022.0373. Epub 2022 Dec 22. |
| 34945016 | Background | Gluszynska P, Lemancewicz D, Dzieciol JB, Razak Hady H. Non-Alcoholic Fatty Liver Disease (NAFLD) and Bariatric/Metabolic Surgery as Its Treatment Option: A Review. J Clin Med. 2021 Dec 7;10(24):5721. doi: 10.3390/jcm10245721. |
| 37567846 | Background | Elhelw O, Ragavan S, Majeed W, Alkhaffaf B, Mohammed N, Senapati S, Ammori BJ, Robinson JA, Syed AA. The impact of bariatric surgery on liver enzymes in people with obesity: A 5-year observational study. Surgeon. 2024 Feb;22(1):e26-e33. doi: 10.1016/j.surge.2023.07.006. Epub 2023 Aug 9. |
| 37088093 | Background | Verrastro O, Panunzi S, Castagneto-Gissey L, De Gaetano A, Lembo E, Capristo E, Guidone C, Angelini G, Pennestri F, Sessa L, Vecchio FM, Riccardi L, Zocco MA, Boskoski I, Casella-Mariolo JR, Marini P, Pompili M, Casella G, Fiori E, Rubino F, Bornstein SR, Raffaelli M, Mingrone G. Bariatric-metabolic surgery versus lifestyle intervention plus best medical care in non-alcoholic steatohepatitis (BRAVES): a multicentre, open-label, randomised trial. Lancet. 2023 May 27;401(10390):1786-1797. doi: 10.1016/S0140-6736(23)00634-7. Epub 2023 Apr 21. |
| 33849437 | Background | Miyake T, Miyazaki M, Yoshida O, Kanzaki S, Nakaguchi H, Nakamura Y, Watanabe T, Yamamoto Y, Koizumi Y, Tokumoto Y, Hirooka M, Furukawa S, Takeshita E, Kumagi T, Ikeda Y, Abe M, Toshimitsu K, Matsuura B, Hiasa Y. Relationship between body composition and the histology of non-alcoholic fatty liver disease: a cross-sectional study. BMC Gastroenterol. 2021 Apr 13;21(1):170. doi: 10.1186/s12876-021-01748-y. |
| 37527759 | Background | Kouvari M, Valenzuela-Vallejo L, Guatibonza-Garcia V, Polyzos SA, Deng Y, Kokkorakis M, Agraz M, Mylonakis SC, Katsarou A, Verrastro O, Markakis G, Eslam M, Papatheodoridis G, George J, Mingrone G, Mantzoros CS. Liver biopsy-based validation, confirmation and comparison of the diagnostic performance of established and novel non-invasive steatotic liver disease indexes: Results from a large multi-center study. Metabolism. 2023 Oct;147:155666. doi: 10.1016/j.metabol.2023.155666. Epub 2023 Jul 30. |
| 28573064 | Background | Hadizadeh F, Faghihimani E, Adibi P. Nonalcoholic fatty liver disease: Diagnostic biomarkers. World J Gastrointest Pathophysiol. 2017 May 15;8(2):11-26. doi: 10.4291/wjgp.v8.i2.11. |
| 32005510 | Background | Ozturk A, Mohammadi R, Pierce TT, Kamarthi S, Dhyani M, Grajo JR, Corey KE, Chung RT, Bhan AK, Chhatwal J, Samir AE. Diagnostic Accuracy of Shear Wave Elastography as a Non-invasive Biomarker of High-Risk Non-alcoholic Steatohepatitis in Patients with Non-alcoholic Fatty Liver Disease. Ultrasound Med Biol. 2020 Apr;46(4):972-980. doi: 10.1016/j.ultrasmedbio.2019.12.020. Epub 2020 Jan 29. |
| 33383965 | Background | Chimoriya R, Piya MK, Simmons D, Ahlenstiel G, Ho V. The Use of Two-Dimensional Shear Wave Elastography in People with Obesity for the Assessment of Liver Fibrosis in Non-Alcoholic Fatty Liver Disease. J Clin Med. 2020 Dec 29;10(1):95. doi: 10.3390/jcm10010095. |
| 31186861 | Background | Noureddin M, Loomba R. Nonalcoholic fatty liver disease: Indications for liver biopsy and noninvasive biomarkers. Clin Liver Dis (Hoboken). 2012 Sep 25;1(4):104-107. doi: 10.1002/cld.65. eCollection 2012 Sep. No abstract available. |
| 24574716 | Background | Sumida Y, Nakajima A, Itoh Y. Limitations of liver biopsy and non-invasive diagnostic tests for the diagnosis of nonalcoholic fatty liver disease/nonalcoholic steatohepatitis. World J Gastroenterol. 2014 Jan 14;20(2):475-85. doi: 10.3748/wjg.v20.i2.475. |
| 25083076 | Background | Nalbantoglu IL, Brunt EM. Role of liver biopsy in nonalcoholic fatty liver disease. World J Gastroenterol. 2014 Jul 21;20(27):9026-37. doi: 10.3748/wjg.v20.i27.9026. |
| 31098621 | Background | Watt MJ, Miotto PM, De Nardo W, Montgomery MK. The Liver as an Endocrine Organ-Linking NAFLD and Insulin Resistance. Endocr Rev. 2019 Oct 1;40(5):1367-1393. doi: 10.1210/er.2019-00034. |
| 35798021 | Background | Riazi K, Azhari H, Charette JH, Underwood FE, King JA, Afshar EE, Swain MG, Congly SE, Kaplan GG, Shaheen AA. The prevalence and incidence of NAFLD worldwide: a systematic review and meta-analysis. Lancet Gastroenterol Hepatol. 2022 Sep;7(9):851-861. doi: 10.1016/S2468-1253(22)00165-0. Epub 2022 Jul 5. |
| 26707365 | Background | Younossi ZM, Koenig AB, Abdelatif D, Fazel Y, Henry L, Wymer M. Global epidemiology of nonalcoholic fatty liver disease-Meta-analytic assessment of prevalence, incidence, and outcomes. Hepatology. 2016 Jul;64(1):73-84. doi: 10.1002/hep.28431. Epub 2016 Feb 22. |
| D004700 | Endocrine System Diseases |
| D005234 | Fatty Liver |
| D008107 | Liver Diseases |
| D004066 | Digestive System Diseases |
| D050177 | Overweight |
| D044343 | Overnutrition |
| D009748 | Nutrition Disorders |
| D001835 | Body Weight |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D000714 |
| Anastomosis, Surgical |
| D013505 | Digestive System Surgical Procedures |
| D001662 | Biliary Tract Surgical Procedures |
| D005763 | Gastroenterostomy |