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  4. Association between genetic risk score and tri-ponderal mass index growth trajectories among different dietary consumption adolescents in a prospective Taiwanese cohort
 
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Association between genetic risk score and tri-ponderal mass index growth trajectories among different dietary consumption adolescents in a prospective Taiwanese cohort

Journal
Nutrition and Metabolism
Journal Volume
19
Journal Issue
1
Date Issued
2022
Author(s)
Wu Y.-F.
KUO-LIONG CHIEN  
Chen Y.-C.
DOI
10.1186/s12986-022-00718-9
URI
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144400102&doi=10.1186%2fs12986-022-00718-9&partnerID=40&md5=6cba60351279631347db02f60994b1c4
https://scholars.lib.ntu.edu.tw/handle/123456789/629421
Abstract
BACKGROUND: Single-nucleotide polymorphisms (SNPs) in various genetic loci are associated with childhood obesity; however, their influence on adolescent growth patterns has rarely been explored. This study investigated whether genetic variants could predict tri-ponderal mass index (TMI)-derived growth trajectories and the interaction between genetic and dietary factors. METHODS: We conducted Taiwan Puberty Longitudinal Study, a prospective cohort that recruited 1,135 children since 2018. Anthropometric measurements were recorded every three months, while dietary nutrition assessment and biological sampling for genotyping were collected during the first visit. TMI growth trajectory groups were identified using growth mixture modeling. A multinomial logistic regression model for different growth trajectories was used to examine the effect of candidate SNPs, and the most related SNPs were used to establish the genetic risk score. We then explored the effect of the genetic risk score in subgroup analysis according to dietary calories and different dietary consumption patterns. RESULTS: Three TMI-based growth trajectory groups were identified among adolescents. The "increased weight" trajectory group accounted for approximately 9.7% of the participants. FTO/rs7206790 was associated with the increased weight growth trajectory after adjusting for the baseline TMI and other correlated covariates (OR: 2.13, 95% CI: 1.08-4.21). We generated the genetic risk score using 4 SNPs (FTO/rs7206790, ADCY9/rs2531995, TFAP2B/rs4715210, and TMEM18/rs6548238) and selected the threshold of 10 points to define risk categories. There were 11.66% and 3.24% of participants belonged to the increased weight trajectory in high- and low-risk groups, respectively; and the predictive ability of the genetic risk score was notable among low calories intake participants (OR: 1.90, 95% CI: 1.18-3.05 vs. OR: 1.17, 95% CI: 0.78-1.75 in high calories intake group). CONCLUSION: Our results offer a new perspective on the genetic and dietary basis of changes in adolescent obesity status. Individualized interventions for obesity prevention may be considered among high-risk children.
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Publisher
BioMed Central Ltd
Type
journal article

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