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| Name | Class |
|---|---|
| Ministry of Science and Technology, Taiwan | OTHER_GOV |
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Children with obesity are prone to suffering from metabolic diseases, which undoubtedly increases the burden of public health. Since obesity is a multiple gene disease, a comprehensive approach using polygenic risk scores (PRS), rather than individual genetic variant, may be a more appropriate method. The aim of the study was to establish a polygenic risk score model to assess differences to assess differences in weight loss treatment outcomes.
The investigators hypothesize that obesity gene variants can predict the efficacy of weight loss intervention in obese children. The aim of the study was to establish a polygenic risk score model to assess differences to assess differences in weight loss treatment outcomes. The investigators will also analyze whether these gene variants have an effect on obesity comorbidities (hypertension, hyperlipidemia, non-alcoholic fatty liver disease, type 2 diabetes, obstructive sleep apnea, polycystic ovary syndrome, etc.). For participants with non-simple obesity, the investigators will collect their complete family history, and perform whole exome sequencing to identify possible rare disease-causing genes.
The experimental design is as follows:
Obese children and adolescent subjects will undergo a 6-month weight loss intervention program and be followed for 12-18 months. The investigators will analyze obesity and fatty liver-related genes in these adolescents using next-generation gene sequencing and/or gene chips, perform polygenic risk score analysis, and use an additive model to total the number of variant loci weighted by effect size. Whole exome gene sequencing refers to the human DNA map (hg19), and Sanger sequencing will be used to confirm the correctness of the variant site.
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| Measure | Description | Time Frame |
|---|---|---|
| weight loss | changes of weight and/or BMI z score | 6 month |
| obesity severity | BMI z score/BMI percentile | 1 month |
| fatty liver | quantification by liver ultrasound/Fibroscan | 1 month |
| Measure | Description | Time Frame |
|---|---|---|
| hyperlipidemia | including triglyceride, HDL cholesterol, total cholesterol | 1 month |
| hypertension | systolic and diastolic blood pressure |
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Inclusion Criteria:
Exclusion Criteria:
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Obese children and adolescents
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Yu-Cheng Lin,, M.D., Ph.D. | Contact | +886-89667000 Ext. 1723 | q92421006@ntu.edu.tw |
| Name | Affiliation | Role |
|---|---|---|
| Yu-Cheng Lin,, M.D., Ph.D. | Far Eastern Memorial Hospital | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Far Eastern Memorial Hospital | Recruiting | New Taipei City | 220 | Taiwan |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 18987268 | Background | Cali AM, Caprio S. Obesity in children and adolescents. J Clin Endocrinol Metab. 2008 Nov;93(11 Suppl 1):S31-6. doi: 10.1210/jc.2008-1363. | |
| 23529041 | Background | El-Sayed Moustafa JS, Froguel P. From obesity genetics to the future of personalized obesity therapy. Nat Rev Endocrinol. 2013 Jul;9(7):402-13. doi: 10.1038/nrendo.2013.57. Epub 2013 Mar 26. |
| Label | URL |
|---|---|
| From obesity genetics to the future of personalized obesity therapy | View source |
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| ID | Term |
|---|---|
| D009765 | Obesity |
| D000096442 | Genetic Risk Score |
| D015431 | Weight Loss |
| ID | Term |
|---|---|
| D050177 | Overweight |
| D044343 | Overnutrition |
| D009748 | Nutrition Disorders |
| D009750 | Nutritional and Metabolic Diseases |
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serum, WBC DNA
| 1 month |
| fasting glucose | hyperglycemia | 1 month |
| HbA1c | hyperglycemia | 1 month |
| 2 hours glucose tolerance test | hyperglycemia | 1 month |
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| 20931363 | Background | Herrera BM, Lindgren CM. The genetics of obesity. Curr Diab Rep. 2010 Dec;10(6):498-505. doi: 10.1007/s11892-010-0153-z. |
| 19506576 | Background | Walley AJ, Asher JE, Froguel P. The genetic contribution to non-syndromic human obesity. Nat Rev Genet. 2009 Jul;10(7):431-42. doi: 10.1038/nrg2594. |
| 33692554 | Background | Wand H, Lambert SA, Tamburro C, Iacocca MA, O'Sullivan JW, Sillari C, Kullo IJ, Rowley R, Dron JS, Brockman D, Venner E, McCarthy MI, Antoniou AC, Easton DF, Hegele RA, Khera AV, Chatterjee N, Kooperberg C, Edwards K, Vlessis K, Kinnear K, Danesh JN, Parkinson H, Ramos EM, Roberts MC, Ormond KE, Khoury MJ, Janssens ACJW, Goddard KAB, Kraft P, MacArthur JAL, Inouye M, Wojcik GL. Improving reporting standards for polygenic scores in risk prediction studies. Nature. 2021 Mar;591(7849):211-219. doi: 10.1038/s41586-021-03243-6. Epub 2021 Mar 10. |
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| A genome-wide association meta-analysis identifies new childhood obesity loci | View source |
| Genomics of disease risk in globally diverse populations | View source |
| The genetics of obesity | View source |
| The genetic contribution to non-syndromic human obesity | View source |
| Improving reporting standards for polygenic scores in risk prediction studies | View source |
| Accuracy of FibroScan Controlled Attenuation Parameter and Liver Stiffness Measurement in Assessing Steatosis and Fibrosis in Patients With Nonalcoholic Fatty Liver Disease. Gastroenterology | View source |
| Polygenic Prediction of Weight and Obesity Trajectories from Birth to Adulthood | View source |
| What reduction in BMI SDS is required in obese adolescents to improve body composition and cardiometabolic health? | View source |
| Genetics of Obesity in East Asians | View source |
| D001835 |
| Body Weight |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D020022 | Genetic Predisposition to Disease |
| D004198 | Disease Susceptibility |
| D020969 | Disease Attributes |
| D010335 | Pathologic Processes |
| D001836 | Body Weight Changes |