TY - JOUR
T1 - Association between genetic risk score and tri-ponderal mass index growth trajectories among different dietary consumption adolescents in a prospective Taiwanese cohort
AU - Wu, Yi Fan
AU - Chien, Kuo Liong
AU - Chen, Yang Ching
N1 - Funding Information:
This study was funded to Chen YC from the Ministry of Science and Technology, Taiwan (Grant Numbers MOST 107-2314-B-038-113-MY3 and MOST 110-2628-B-038-014 and MOST 111-2628-B-038-022). This organization had no role in the study design, data analysis, or writing of this article.
Publisher Copyright:
© 2022, The Author(s).
PY - 2022/12
Y1 - 2022/12
N2 - 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.
AB - 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.
KW - Adolescent growth trajectories
KW - Gene-diet interaction
KW - Single-nucleotide polymorphism
KW - Tri-ponderal mass index
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U2 - 10.1186/s12986-022-00718-9
DO - 10.1186/s12986-022-00718-9
M3 - Article
AN - SCOPUS:85144400102
SN - 1743-7075
VL - 19
JO - Nutrition and Metabolism
JF - Nutrition and Metabolism
IS - 1
M1 - 83
ER -