Polygenic Risk Score to Predict Weight Loss Intervention in Children With Obesity

Development of Polygenic Risk Score to Predict the Efficacy of Weight Loss Intervention in Children and Adolescents With Obesity

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.

Study Overview

• Status: Recruiting
• Conditions: Obesity; Children

Detailed Description

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.

• Study Type: Observational
• Enrollment (Estimated): 300

Contacts and Locations

• Study Contact: Name: Yu-Cheng Lin,, M.D., Ph.D.; Phone Number: +886-89667000 Ext. 1723; Email: q92421006@ntu.edu.tw

Study Locations

• Taiwan
  • New Taipei City, Taiwan, 220
    • Recruiting
    • Far Eastern Memorial Hospital
    • Contact: Yu-Cheng Lin, M.D., Ph.D.; Phone Number: 1723 886-89667000; Email: q92421006@ntu.edu.tw
    • Principal Investigator: Yu-Cheng Lin, M.D., Ph.D.

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 1 second to 18 years (Child, Adult)
• Accepts Healthy Volunteers: No

• Sampling Method: Probability Sample

Study Population

Obese children and adolescents

Description

Inclusion Criteria:

• Age <18 years old
• Obesity definition: BMI > 95% according to the age- and gender-specific standard by National Health Institute in Taiwan
• Willing to give written informed consent

Exclusion Criteria:

• Alcohol consumption
• Major systemic diseases, including cardiopulmonary disease, renal failure, cancer, and major psychotic disorder

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	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

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
hyperlipidemia	including triglyceride, HDL cholesterol, total cholesterol	1 month
hypertension	systolic and diastolic blood pressure	1 month
fasting glucose	hyperglycemia	1 month
HbA1c	hyperglycemia	1 month
2 hours glucose tolerance test	hyperglycemia	1 month

Collaborators and Investigators

• Sponsor: Far Eastern Memorial Hospital
• Collaborators: Ministry of Science and Technology, Taiwan
• Investigators: Principal Investigator: Yu-Cheng Lin,, M.D., Ph.D., Far Eastern Memorial Hospital

Publications and helpful links

General Publications

• Ford AL, Hunt LP, Cooper A, Shield JP. What reduction in BMI SDS is required in obese adolescents to improve body composition and cardiometabolic health? Arch Dis Child. 2010 Apr;95(4):256-61. doi: 10.1136/adc.2009.165340. Epub 2009 Dec 4.
• 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.
• 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. Erratum In: Nat Rev Endocrinol. 2014 Jan;10(1):4.
• Bradfield JP, Taal HR, Timpson NJ, Scherag A, Lecoeur C, Warrington NM, Hypponen E, Holst C, Valcarcel B, Thiering E, Salem RM, Schumacher FR, Cousminer DL, Sleiman PM, Zhao J, Berkowitz RI, Vimaleswaran KS, Jarick I, Pennell CE, Evans DM, St Pourcain B, Berry DJ, Mook-Kanamori DO, Hofman A, Rivadeneira F, Uitterlinden AG, van Duijn CM, van der Valk RJ, de Jongste JC, Postma DS, Boomsma DI, Gauderman WJ, Hassanein MT, Lindgren CM, Magi R, Boreham CA, Neville CE, Moreno LA, Elliott P, Pouta A, Hartikainen AL, Li M, Raitakari O, Lehtimaki T, Eriksson JG, Palotie A, Dallongeville J, Das S, Deloukas P, McMahon G, Ring SM, Kemp JP, Buxton JL, Blakemore AI, Bustamante M, Guxens M, Hirschhorn JN, Gillman MW, Kreiner-Moller E, Bisgaard H, Gilliland FD, Heinrich J, Wheeler E, Barroso I, O'Rahilly S, Meirhaeghe A, Sorensen TI, Power C, Palmer LJ, Hinney A, Widen E, Farooqi IS, McCarthy MI, Froguel P, Meyre D, Hebebrand J, Jarvelin MR, Jaddoe VW, Smith GD, Hakonarson H, Grant SF; Early Growth Genetics Consortium. A genome-wide association meta-analysis identifies new childhood obesity loci. Nat Genet. 2012 May;44(5):526-31. doi: 10.1038/ng.2247.
• Gurdasani D, Barroso I, Zeggini E, Sandhu MS. Genomics of disease risk in globally diverse populations. Nat Rev Genet. 2019 Sep;20(9):520-535. doi: 10.1038/s41576-019-0144-0. Epub 2019 Jun 24. Erratum In: Nat Rev Genet. 2019 Jul 3;:
• Holzapfel C, Sag S, Graf-Schindler J, Fischer M, Drabsch T, Illig T, Grallert H, Stecher L, Strack C, Caterson ID, Jebb SA, Hauner H, Baessler A. Association between Single Nucleotide Polymorphisms and Weight Reduction in Behavioural Interventions-A Pooled Analysis. Nutrients. 2021 Mar 2;13(3):819. doi: 10.3390/nu13030819.
• Heitkamp M, Siegrist M, Molnos S, Brandmaier S, Wahl S, Langhof H, Grallert H, Halle M. Obesity Genes and Weight Loss During Lifestyle Intervention in Children With Obesity. JAMA Pediatr. 2021 Jan 1;175(1):e205142. doi: 10.1001/jamapediatrics.2020.5142. Epub 2021 Jan 4.
• Herrera BM, Lindgren CM. The genetics of obesity. Curr Diab Rep. 2010 Dec;10(6):498-505. doi: 10.1007/s11892-010-0153-z.
• 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.
• 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.
• Eddowes PJ, Sasso M, Allison M, Tsochatzis E, Anstee QM, Sheridan D, Guha IN, Cobbold JF, Deeks JJ, Paradis V, Bedossa P, Newsome PN. Accuracy of FibroScan Controlled Attenuation Parameter and Liver Stiffness Measurement in Assessing Steatosis and Fibrosis in Patients With Nonalcoholic Fatty Liver Disease. Gastroenterology. 2019 May;156(6):1717-1730. doi: 10.1053/j.gastro.2019.01.042. Epub 2019 Jan 25.
• Khera AV, Chaffin M, Wade KH, Zahid S, Brancale J, Xia R, Distefano M, Senol-Cosar O, Haas ME, Bick A, Aragam KG, Lander ES, Smith GD, Mason-Suares H, Fornage M, Lebo M, Timpson NJ, Kaplan LM, Kathiresan S. Polygenic Prediction of Weight and Obesity Trajectories from Birth to Adulthood. Cell. 2019 Apr 18;177(3):587-596.e9. doi: 10.1016/j.cell.2019.03.028.
• Sun C, Kovacs P, Guiu-Jurado E. Genetics of Obesity in East Asians. Front Genet. 2020 Oct 20;11:575049. doi: 10.3389/fgene.2020.575049. eCollection 2020.

Helpful Links

• Obesity in children and adolescents
• From obesity genetics to the future of personalized obesity therapy
• A genome-wide association meta-analysis identifies new childhood obesity loci
• Genomics of disease risk in globally diverse populations
• Association between Single Nucleotide Polymorphisms and Weight Reduction in Behavioural Interventions-A Pooled Analysis
• Obesity Genes and Weight Loss During Lifestyle Intervention in Children With Obesity
• The genetics of obesity
• The genetic contribution to non-syndromic human obesity
• Improving reporting standards for polygenic scores in risk prediction studies
• Accuracy of FibroScan Controlled Attenuation Parameter and Liver Stiffness Measurement in Assessing Steatosis and Fibrosis in Patients With Nonalcoholic Fatty Liver Disease. Gastroenterology
• Polygenic Prediction of Weight and Obesity Trajectories from Birth to Adulthood
• What reduction in BMI SDS is required in obese adolescents to improve body composition and cardiometabolic health?
• Genetics of Obesity in East Asians

Study record dates

Study Major Dates

• Study Start (Actual): June 1, 2022
• Primary Completion (Estimated): July 31, 2025
• Study Completion (Estimated): July 31, 2025

Study Registration Dates

• First Submitted: July 11, 2022
• First Submitted That Met QC Criteria: July 19, 2022
• First Posted (Actual): July 20, 2022

Study Record Updates

• Last Update Posted (Actual): September 13, 2023
• Last Update Submitted That Met QC Criteria: September 12, 2023
• Last Verified: September 1, 2023

More Information

Terms related to this study

• Keywords: weight loss; whole exome sequencing; polygenic risk score
• Additional Relevant MeSH Terms: Overnutrition; Nutrition Disorders; Overweight; Body Weight; Body Weight Changes; Obesity; Weight Loss
• Other Study ID Numbers: 111078-F

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No