Stability of proposed biomarkers of prenatal androgen exposure over the menstrual cycle
Published in Journal of Developmental Origins of Health and Disease, April 1, 2015 | Online publication on January 13, 2015
Author(s): Emily S Barrett, Lauren E Parlett, Shanna H Swan
DOI: 10.1017/S2040174414000646 | Pubmed ID: 25584807
Abstract
The prenatal hormonal milieu is widely believed to shape health later in life; however, there are considerable methodological challenges associated with measuring the in utero hormonal environment. Two potential biomarkers of prenatal androgen exposure that can be measured postnatally have been proposed: anogenital distance (AGD) and the ratio of the second to fourth digits of the hand (2D:4D). Although both measures are widely used research tools, their use in adult women may be complicated by the dramatic fluctuations in reproductive hormones across the menstrual cycle. To determine whether there is cyclical variation in these biomarkers, we conducted a longitudinal study of 12 naturally cycling, nulliparous adult women. Trained examiners assessed two measures of AGD [anus to clitoris (AGD-AC) and anus to fourchette (AGD-AF)] and 2D:4D in both hands for the duration of three menstrual cycles, taking measurements during the follicular, peri-ovulatory and luteal phases of each cycle. Despite the small sample size, longer (more masculine) AGD was associated with lower (more masculine) digit ratios, as predicted by the literature. Using multi-level linear regression models, we found that AGD and 2D:4D measurements did not differ significantly across cycle phases. AGD-AF and digit ratios in both hands were associated with age at menarche, suggesting a possible common developmental trajectory. These results demonstrate that AGD and 2D:4D are stable across the menstrual cycle. In addition, research is needed to determine how reliably these measures reflect the in utero hormonal milieu.
Keywords: prenatal androgens.
Funding Transparency
No funding has been identified for this publication.
Tags
Analytic: multivariable regression
Data Source: anthropometry
Research Focus: reproductive epidemiology
Study Design: cohort study
Entry last updated (DMY): 10-11-2024.