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Developmental programming of growth: Genetic variant in GH2 gene encoding placental growth hormone contributes to adult height determination

Publication at First Faculty of Medicine |
2013

Abstract

Introduction: Given the physiological role of placental growth hormone (PGH) during intrauterine development and growth, genetic variation in the coding Growth hormone 2 (GH2) gene may modulate developmental programming of adult stature. Two major GH2 variants were described worldwide, determined by single polymorphism (rs2006123; c.171 + 50C > A).

We sought to study whether GH2 variants may contribute to adult anthropometric measurements. Methods: Genotyping of GH2 SNP rs2006123 by RFLP, testing its genetic association with adult height and Body Mass Index (BMI) by linear regression analysis, and combining the results of three individual study samples in meta-analysis.

Study samples: HYPEST (Estonia), n = 1464 (506 men/958 women), CADCZ (Czech), n = 871 (518/353); UFA (Bashkortostan), n = 954 (655/299); meta-analysis, n = 3289 (1679/1610). Results: Meta-analysis across HYPEST, CADCZ and UFA samples (n = 3289) resulted in significant association of GH2 rs2006123 with height (recessive model: AA-homozygote effect: beta (SE) = 1.26 (0.46), P = 5.90 x 10(-3); additive model: A-allele effect: beta (SE) = 0.45 (0.18), P = 1.40 x 10(-2)).

Among men (n = 1679), the association of the A-allele with taller stature remained significant after multiple-testing correction (additive effect: beta = 0.86 (0.28), P = 1.83 x 10(-3)). No association was detected with BMI.

Notably, rs2006123 was in strong LD (r(2) >= 0.87) with SNPs significantly associated with height (rs2665838, rs7209435, rs11658329) and mapped near GH2 in three independent meta-analyses of GWA studies. Conclusions: This is the first study demonstrating a link between a placental gene variant and programming of growth potential in adulthood.

The detected association between PGH encoding GH2 and adult height promotes further research on the role of placental genes in prenatal programming of human metabolism. (C) 2013 The Authors. Published by Elsevier Ltd.

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