ObesityNCT05466097
Polygenic Risk Score to Predict Weight Loss Intervention in Children With Obesity
An observational study of Obesity and Children, run by Far Eastern Memorial Hospital at 1 site in Taiwan.
Trial summary
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. Read more about this study
- Who is it for?
- Ages Up to 18 years
- How many people
- 300 participants
- Where
- 1 siteTaiwan
- Study dates
- 1 Jun 2022to 31 Jul 2025
- How long will I take part?
- 6 Months
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Up to 18 years
- All sexes
- No healthy volunteers
- Child, Adult
Study population: Obese children and adolescents
Who may be able to join
- 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
Who cannot join
- Alcohol consumption
- Major systemic diseases, including cardiopulmonary disease, renal failure, cancer, and major psychotic disorder
Trial locations and contacts
1 site in 1 country.
Taiwan1 site, 1 recruiting
- Recruiting
Far Eastern Memorial Hospital
New Taipei City, 220
Yu-Cheng Lin, M.D., Ph.D., 886-89667000 ext. 1723, q92421006@ntu.edu.tw
Yu-Cheng Lin, M.D., Ph.D.
About this study
Official title: 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.
Read the 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.
- Keywords
- whole exome sequencing, polygenic risk score, weight loss
- Medical subject headings
- Obesity, Genetic Risk Score, Weight Loss
What is being measured
The primary outcome is the main question the study is designed to answer.
weight loss
changes of weight and/or BMI z score
Measured: 6 month
obesity severity
BMI z score/BMI percentile
Measured: 1 month
fatty liver
quantification by liver ultrasound/Fibroscan
Measured: 1 month
Secondary outcomes (5)
hyperlipidemia
including triglyceride, HDL cholesterol, total cholesterol
Measured: 1 month
hypertension
systolic and diastolic blood pressure
Measured: 1 month
fasting glucose
hyperglycemia
Measured: 1 month
HbA1c
hyperglycemia
Measured: 1 month
2 hours glucose tolerance test
hyperglycemia
Measured: 1 month
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted20 Jul 2022
- Study start1 Jun 2022
- Primary completion31 Jul 2025 (estimated)
- Study completion31 Jul 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (13)Papers the sponsor has linked to this study.
- Other trials for ObesityStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 300 participants (estimated)
- Target duration
- 6 Months
Sponsor and investigators
- Lead sponsor
- Far Eastern Memorial Hospital
- Sponsor type
- University, hospital or other
- Collaborators
- Ministry of Science and Technology, Taiwan
- Responsible party
- Sponsor
- Investigators
- Yu-Cheng Lin,, M.D., Ph.D., Principal investigator, Far Eastern Memorial Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05466097
- Sponsor's protocol ID
- 111078-F
- Status last verified
- Sep 2023
- First submitted
- 11 Jul 2022
- Last updated
- 13 Sep 2023
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Publications
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.
PubMed 18987268El-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.
PubMed 23529041Bradfield 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.
PubMed 22484627Gurdasani 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.
PubMed 31235872Holzapfel 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.
PubMed 33801339Heitkamp 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.
PubMed 33315090Herrera BM, Lindgren CM. The genetics of obesity. Curr Diab Rep. 2010 Dec;10(6):498-505. doi: 10.1007/s11892-010-0153-z.
PubMed 20931363Walley 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.
PubMed 19506576Wand 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.
PubMed 33692554Eddowes 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.
PubMed 30689971Khera 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.
PubMed 31002795Ford 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.
PubMed 19966092Sun 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.
PubMed 33193685
Study at a glance
From the registry record, last updated by the sponsor on 13 Sep 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development of Polygenic Risk Score to Predict the Efficacy of Weight Loss Intervention in Children and Adolescents With Obesity
- ClinicalTrials.gov ID
- NCT05466097
- Acronym / sponsor ID
- 111078-F
- Keywords
- whole exome sequencing, polygenic risk score, weight loss
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 300 participants (estimated)
- Lead sponsor
- Far Eastern Memorial HospitalUniversity, hospital or other
- Collaborators
- Ministry of Science and Technology, Taiwan
- Study start
- 1 Jun 2022 (actual)
- Primary completion
- 31 Jul 2025 (estimated)
- Study completion
- 31 Jul 2025 (estimated)
- First posted
- 20 Jul 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
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 design
- Observational model
- Cohort
- Time perspective
- Prospective
- Target follow-up
- 6 Months
Who may qualify
- Ages
- Up to 18 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult
- Study population
- Obese children and adolescents
Key inclusion criteria (3 listed)
- 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
Key exclusion criteria (2 listed)
- Alcohol consumption
- Major systemic diseases, including cardiopulmonary disease, renal failure, cancer, and major psychotic disorder
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
weight loss
Time frame: 6 month
changes of weight and/or BMI z score
obesity severity
Time frame: 1 month
BMI z score/BMI percentile
fatty liver
Time frame: 1 month
quantification by liver ultrasound/Fibroscan
5 secondary outcomes
hyperlipidemia
Time frame: 1 month
hypertension
Time frame: 1 month
fasting glucose
Time frame: 1 month
HbA1c
Time frame: 1 month
2 hours glucose tolerance test
Time frame: 1 month
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 13 Sep 2023.
- Background: PubMed 18987268Cali 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.
- Background: PubMed 23529041El-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.
- Background: PubMed 22484627Bradfield 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.
- Background: PubMed 31235872Gurdasani 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.
- Background: PubMed 33801339Holzapfel 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.
- Background: PubMed 33315090Heitkamp 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.
- Background: PubMed 20931363Herrera BM, Lindgren CM. The genetics of obesity. Curr Diab Rep. 2010 Dec;10(6):498-505. doi: 10.1007/s11892-010-0153-z.
- Background: PubMed 19506576Walley 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.
- Background: PubMed 33692554Wand 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.
- Background: PubMed 30689971Eddowes 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.
- Background: PubMed 31002795Khera 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.
- Background: PubMed 19966092Ford 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.
- From obesity genetics to the future of personalized obesity therapyLink provided by the sponsor.
- A genome-wide association meta-analysis identifies new childhood obesity lociLink provided by the sponsor.
- Genomics of disease risk in globally diverse populationsLink provided by the sponsor.
- The genetics of obesityLink provided by the sponsor.
- The genetic contribution to non-syndromic human obesityLink provided by the sponsor.
- Improving reporting standards for polygenic scores in risk prediction studiesLink provided by the sponsor.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Yu-Cheng Lin,, M.D., Ph.D. principal investigator
Far Eastern Memorial Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Obesity and Children, run by Far Eastern Memorial Hospital at 1 site in Taiwan.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 13 Sep 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Taiwan. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Yu-Cheng Lin,, M.D., Ph.D. (+886-89667000 Ext. 1723, q92421006@ntu.edu.tw), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
weight loss (time frame: 6 month). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05466097, which also lists 13 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 13 Sep 2023.