Amniotic fluid metabolic biomarkers of fetal physiology and pregnancy success

Amniotic fluid (AF) profiling provides a minimally invasive window into early fetal physiology. We characterized the AF metabolome from first trimester (Day 68) Holstein dairy heifers (n = 45), considering fetal sex, conception method [in vitro fertilization vs. artificial insemination (AI)], and eventual pregnancy outcome as key variables. Multivariate statistics uncovered differentially abundant metabolites for each comparison-including markers that preceded spontaneous abortion-independently of recipient age, weight, gestation length, or fetal genetics. Thereafter, a machine learning algorithm using panels of six metabolites accurately predicted fetal sex (AUROC = 0.76; P = 0.023) and pregnancy viability (AUROC = 0.81; P = 0.018), while corroborating conception method (AUROC = 0.91; P = 0.001). External validation using AF (Day 42) from an independent cohort of beef heifers (n = 22) reproduced the fetal sex classifier with similarly high sensitivity and specificity (AUROC = 0.85, P = 0.029). These findings reveal metabolic signatures that forecast fetal sex and pregnancy viability, while confirming distinct metabolic imprints of assisted-conception modalities. These data lay the groundwork for next-generation AF prenatal diagnostics in veterinary and human obstetrics.