Genetic determinants of BMI from early childhood to adolescence: the Santiago Longitudinal Study
Author
dc.contributor.author
Justice, A. E.
Author
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Chittoor, G.
Author
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Blanco, E.
Author
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Graff, M.
Author
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Wang, Y.
Author
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Albala Brevis, Cecilia
Author
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Santos, J. L.
Author
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Angel, B.
Author
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Lozoff, B.
Author
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Voruganti, V. S.
Author
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North, K. E.
Author
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Gahagan, S.
Admission date
dc.date.accessioned
2019-10-14T15:41:02Z
Available date
dc.date.available
2019-10-14T15:41:02Z
Publication date
dc.date.issued
2019
Cita de ítem
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Pediatric Obesity, Volumen 14, Issue 3, 2019
Identifier
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20476310
Identifier
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20476302
Identifier
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10.1111/ijpo.12479
Identifier
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https://repositorio.uchile.cl/handle/2250/171514
Abstract
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Background: While the genetic contribution to obesity is well established,
few studies have examined how genetic variants influence standardized body mass
index Z-score (BMIz) in Hispanics/Latinos, especially across childhood and
adolescence.
Objectives: We estimated the effect of established BMIz loci in Chilean children
of the Santiago Longitudinal Study (SLS).
Methods: We examined associations with BMIz at age 10 for 15 loci previously
identified in European children. For significant loci, we performed association analyses
at ages 5 and 16 years, for which we have smaller sample sizes. We tested associations
of unweighted genetic risk scores (GRSs) for previously identified tag
variants (GRS_EUR) and from the most significant variants in SLS at each locus
(GRS_SLS).
Results: We generalized five variants at age 10 (P < 0.05 and directionally consistent),
including rs543874 that reached Bonferroni-corrected significance. The effect
on BMIz was greatest at age 10 for all significant loci, except FTO, which
exhibited an increase in effect from ages 5 to 16. Both GRSs were associated with
BMIz (P < 0.0001), but GRS_SLS explained a much greater proportion of the variation
(13.63%).
Conclusion: Our results underscore the importance of conducting genetic investigations
across life stages and selecting ancestry appropriate tag variants in future
studies for disease prediction and clinical evaluation.