Sex-specific effects of prenatal metal exposure on child anogenital distance: an advanced computational analysis

Abstract

Whether prenatal metal mixtures exert sex-dependent effects on anogenital distance (AGD) - a biomarker of prenatal androgen action - remains unknown. To address this gap, we conducted a prospective cohort study of 248 mother-infant pairs, measuring 10 metals in first-trimester maternal plasma and AGD at age 2 years. To evaluate the associations and identify the most important metal contributors, we combined single-metal linear regression with three complementary advanced computational approaches (extreme gradient boosting, Bayesian additive regression trees, Bayesian kernel machine regression). We further applied propensity score stratification and overlap weighting to strengthen causal inference. The analyses revealed sex-specific patterns: in males, cadmium (Cd), thallium (Tl), and arsenic (As) were inversely associated with anopenile distance (AGD-AP), with Cd showing the strongest effect (-6.96%, P_FDR = 0.013), followed by As (-2.83%, P_FDR = 0.033) and Tl (-2.16%, P_FDR = 0.040). In females, nickel (Ni) was suggestively positively associated with anoclitoral distance (AGD-AC) (6.94%, P = 0.014), though not significant after false discovery rate correction. Machine learning identified Tl and Cd as the top predictors in males, and As in females. These associations were supported by propensity score-based sensitivity analyses, particularly for male Tl and Cd. No significant associations were found for AGD-AS/AGD-AF in either sex. These findings demonstrate that prenatal metal exposure exerts sex-specific opposing effects on AGD, with Cd and Tl in males showing the most robust inverse associations. Our results highlight the value of integrating machine learning with traditional epidemiological approaches and underscore the importance of sex-stratified analyses in mixture exposure analysis.

Keywords

Heavy metals / anogenital distance / prenatal exposure / machine learning / sex-specific effects

References

[1] Jalil A,Iram S.A systematic review: global trend in heavy metal concentration in vegetables, dietary exposure, and health risk assessment.Environ Monit Assess2026;198:252

[2] Jiao L,Stein A,Zhang P.A framework for unveiling multi-pathway mechanisms of soil heavy metal pollution: evidence from five major urban agglomerations in China.J Environ Manage2026;401:128952

[3] Xiao N,Wang Y,Shen C.Four decades of global cereal lead contamination patterns.Ecotoxicol Environ Saf2026;309:119687

[4] Duarte NAA,Maraslis FT.Blood-based transcriptomic profiles associated with chronic mercury exposure in Amazonian riverine populations.J Hazard Mater2026;504:141273

[5] Jomova K,Nepovimova E,Valko M.Heavy metals: toxicity and human health effects.Arch Toxicol2025;99:153-209 PMCID:PMC11742009

[6] Kinjo, Y.; Shibata, E.; Askew, D. J.; Japan Environment and Children’s Study Group. Association of placental weight at birth with maternal whole blood concentration of heavy metals (cadmium, lead, mercury, selenium, and manganese): The Japan Environment and Children’s Study (JECS).Environ Int2024;188:108725

[7] Zhou J,Chen S.Placental transfer efficiency of metals and its association with cognitive development in offspring: roles of placental inflammatory cytokines and oxidative stress markers.J Hazard Mater2025;500:140380

[8] Yu G,Tan YQ.Gestational exposure to metals and small vulnerable newborns: a systematic review and meta-analysis.Environ Int2026;208:110052

[9] Adibi JJ,Koistinen H.Molecular pathways in placental-fetal development and disruption.Mol Cell Endocrinol2024;581:112075 PMCID:PMC10958409

[10] Andonotopo W,Dewantiningrum J.Endocrine disrupting chemicals: translating mechanisms into perinatal risk assessment.J Perinat Med2025;53:1238-52

[11] Grandjean P.Developmental neurotoxicity of industrial chemicals.Lancet2006;368:2167-78

[12] Barouki R,Grandjean P,Heindel JJ.Developmental origins of non-communicable disease: implications for research and public health.Environ Health2012;11:42 PMCID:PMC3384466

[13] Gu J,Wu G.Correlation between essential and toxic elements in maternal blood during early pregnancy and atrial septal defects/ventricular septal defects/patent ductus arteriosus in offspring.Birth Defects Res2024;116:e2282

[14] Barrett ES,Getz K.Protective role of the placental efflux transporter BCRP/ABCG2 in the relationship between prenatal cadmium exposure, placenta weight, and size at birth.Environ Res2023;225:115597 PMCID:PMC10091184

[15] Barrett ES,Thurston SW.Associations of exposure to air pollution during the male programming window and mini-puberty with anogenital distance and penile width at birth and at 1 year of age in the multicenter U.S. TIDES cohort.Environ Health Perspect2023;131:117001 PMCID:PMC10648757

[16] Cajachagua-Torres KN,Seok E.Prenatal phthalate exposure and anogenital distance in infants at 12 months.Environ Int2025;199:109472 PMCID:PMC12086046

[17] Barrett ES,Mbowe O.First-trimester urinary bisphenol A concentration in relation to anogenital distance, an androgen-sensitive measure of reproductive development, in infant girls.Environ Health Perspect2017;125:077008 PMCID:PMC5744699

[18] Bornehag CG,Jönsson BA.Prenatal phthalate exposures and anogenital distance in Swedish boys.Environ Health Perspect2015;123:101-7 PMCID:PMC4286276

[19] Nelson W,Yang Y,Wang YX.In utero exposure to persistent and nonpersistent endocrine-disrupting chemicals and anogenital distance. A systematic review of epidemiological studies†.Biol Reprod2020;102:276-91

[20] Andreasen SM,Hagen CP.Correlation of anogenital distance from childhood to age 9 years-a prospective population-based birth cohort-the Odense Child Cohort.Hum Reprod Open2024;2024:hoae050 PMCID:PMC11415829

[21] Zamani P,Kelishadi R,Dianatinasab M.Association between anogenital distance as a noninvasive index in the diagnosis and prognosis of reproductive disorder: a systematic review.Int J Reprod Biomed2023;21:599-618 PMCID:PMC10598470

[22] Barrett ES,Sathyanarayana S.Anogenital distance in newborn daughters of women with polycystic ovary syndrome indicates fetal testosterone exposure.J Dev Orig Health Dis2018;9:307-14 PMCID:PMC5997496

[23] Dural O,Yasa C.Idiopathic primary ovarian insufficiency is associated with anogenital distance, a marker for prenatal environment.Eur J Obstet Gynecol Reprod Biol2021;258:304-8

[24] Kulaksiz D.The relationship between anogenital distance and female sexual life.Minerva Obstet Gynecol2023;75:311-5

[25] Celik M,Yalcin SS.Perinatal exposure to heavy metals and trace elements of preterm neonates in the NICU: a toxicological study using multiple biomatrices.Toxics2025;13:898 PMCID:PMC12568181

[26] Huang L,Luo X.Associations of prenatal exposure to multiple metals with testicular volume and anogenital distance in infant boys: a longitudinal cohort study.Environ Int2020;143:105900

[27] Chen T.XGBoost: a scalable tree boosting system. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Min. Association for Computing Machinery; 2016. pp. 785-94.

[28] Chipman HA,McCulloch RE.BART: Bayesian additive regression trees.Ann Appl Stat2010;4:266-98

[29] Bobb JF,Claus Henn B.Bayesian kernel machine regression for estimating the health effects of multi-pollutant mixtures.Biostatistics2015;16:493-508 PMCID:PMC5963470

[30] Bobb JF,Valeri L.Statistical software for analyzing the health effects of multiple concurrent exposures via Bayesian kernel machine regression.Environ Health2018;17:67 PMCID:PMC6102907

[31] Xie Y,Zheng D.Associations of prenatal metal exposure with child neurodevelopment and mediation by perturbation of metabolic pathways.Nat Commun2025;16:2089 PMCID:PMC11873229

[32] Hu J,Zheng T.Prenatal metal mixture exposure and birth weight: a two-stage analysis in two prospective cohort studies.Eco Environ Health2022;1:165-71 PMCID:PMC10702918

[33] Chen X,Zhou A.Fetal weight growth trajectories and childhood development: a population-based cohort study.Sci Bull2024;69:3404-14

[34] Jia Z,Yu L.Prenatal lead exposure, genetic factors, and cognitive developmental delay.JAMA Netw Open2023;6:e2339108 PMCID:PMC10594149

[35] Sathyanarayana, S.; Grady, R.; Redmon, J. B.; et al.; TIDES Study Team. Anogenital distance and penile width measurements in The Infant Development and the Environment Study (TIDES): methods and predictors.J Pediatr Urol2015;11:76.e1-6 PMCID:PMC4456209

[36] Olapeju B,Wang G.Birth outcomes across the spectrum of maternal age: dissecting aging effect versus confounding by social and medical determinants.BMC Pregnancy Childbirth2021;21:594 PMCID:PMC8411515

[37] Blomberg M,Kjølhede P.Impact of maternal age on obstetric and neonatal outcome with emphasis on primiparous adolescents and older women: a Swedish Medical Birth Register Study.BMJ Open2014;4:e005840 PMCID:PMC4244420

[38] Vandekerckhove M,Civadier MS,Bouyer J.Impact of maternal age on obstetric and neonatal morbidity: a retrospective cohort study.BMC Pregnancy Childbirth2021;21:732 PMCID:PMC8555100

[39] Wilcox AJ,Basso O.On the pitfalls of adjusting for gestational age at birth.Am J Epidemiol2011;174:1062-8 PMCID:PMC3243938

[40] Liu X,Wang G,Wang W.Effect of pre-pregnancy body mass index on adverse pregnancy outcome in north of China.Arch Gynecol Obstet2011;283:65-70

[41] Li S,Du L.Association between parity and adverse maternal and neonatal outcomes: a population-based cross-sectional study.Front Med2025;12:1697655 PMCID:PMC12682818

[42] Li L,Yang Y,Zhuang Y.Maternal educational inequalities about adverse pregnancy outcomes observed in a rural area of a province of China during a time period (2010-2018).J Epidemiol Community Health2022;76:458-65

[43] Yen FS,Wu YL.Impact of family income on the development of gestational diabetes mellitus and the associated birth outcomes: a nationwide study.J Diabetes Investig2025;16:51-9 PMCID:PMC11693567

[44] Barrera-Gómez J.Models with transformed variables: interpretation and software.Epidemiology2015;26:e16-7

[45] Linden A.A comparison of approaches for stratifying on the propensity score to reduce bias.J Eval Clin Pract2017;23:690-6

[46] Thomas LE,Li F.Addressing substantial covariate imbalance with propensity score stratification and balancing weights: connections and recommendations.Epidemiol Methods2023;12:20220131 PMCID:PMC10637625

[47] Li F,Li F.Addressing extreme propensity scores via the overlap weights.Am J Epidemiol2019;188:250-7

[48] Wen J,Lu R.Associations between seminal plasma metals/metalloids and semen quality: a cross-sectional study.Ecotoxicol Environ Saf2024;279:116472

[49] Chedrese PJ,Henson MC.Cadmium as an endocrine disruptor in the reproductive system.Immunol Endocr Metab Agents Med Chem2006;6:27-35

[50] Alamdar A,Huang Q.Enhanced histone H3K9 tri-methylation suppresses steroidogenesis in rat testis chronically exposed to arsenic.Ecotoxicol Environ Saf2019;170:513-20

[51] Branch FM,Chen Z.Metal(loid)s and human semen quality: the LIFE Study.Reprod Toxicol2021;106:94-102 PMCID:PMC12432002

[52] Culty M.Antiandrogens and male reproduction.Encyclopedia of Reproduction2026. pp. 813-22

[53] Chaturvedi NK,Negi S.Endocrine disruptors provoke differential modulatory responses on androgen receptor and pregnane and xenobiotic receptor: potential implications in metabolic disorders.Mol Cell Biochem2010;345:291-308

[54] Li H,Huang L.Hexavalent chromium inhibits testosterone synthesis in bovine testicular leydig cells through mitochondrial damage via BNIP3.Reprod Biol2026;26:101181

[55] Shobana N,Navin AK,Aruldhas MM.Prenatal exposure to excess chromium attenuates transcription factors regulating expression of androgen and follicle stimulating hormone receptors in Sertoli cells of prepuberal rats.Chem Biol Interact2020;328:109188

[56] Kong L,Zhang T.Nickel nanoparticles exposure and reproductive toxicity in healthy adult rats.Int J Mol Sci2014;15:21253-69 PMCID:PMC4264223

[57] Ashrap P,Téllez-Rojo MM.In utero and peripubertal metals exposure in relation to reproductive hormones and sexual maturation and progression among girls in Mexico City.Environ Res2019;177:108630 PMCID:PMC6734930

[58] Hill, J.; Linero, A.; Murray, J. Bayesian additive regression trees: a review and look forward. Ann. Rev. Stat. Appl. 2020, 7, 251-78.

[59] Kou M,Wang M.Cadmium and lead ions interaction: a model for assessing combined heavy metal contamination in soils for food safety risk evaluation.Ecotoxicol Environ Saf2025;298:118324

[60] Obeng-Gyasi E.Association of combined lead, cadmium, and mercury with systemic inflammation.Front Public Health2024;12:1385500 PMCID:PMC11390544

[61] Schisterman EF,Platt RW.Overadjustment bias and unnecessary adjustment in epidemiologic studies.Epidemiology2009;20:488-95 PMCID:PMC2744485

[62] Thomas LE,Pencina MJ.Overlap weighting: a propensity score method that mimics attributes of a randomized clinical trial.JAMA2020;323:2417-8

[63] Rosen EM,McNell EE.Variability and longitudinal trajectories of phthalate and replacement biomarkers across pregnancy in the human placenta and phthalates study.Environ Sci Technol2023;57:13036-46 PMCID:PMC10513743

[64] Bartell SM,Rhee J,Rusiecki J.How well does a single blood sample represent long-term exposure for epidemiological studies of PFOA among men in the general population?.Environ Int2024;192:109056

[65] Thankamony A,Ong KK,Hughes IA.Anogenital distance as a marker of androgen exposure in humans.Andrology2016;4:616-25 PMCID:PMC6225986

[66] Cortes D,Hildorf AE.Anogenital distance in a cohort of 169 infant boys with uni- or bilateral cryptorchidism including 18 boys with vanishing testes.Hum Reprod2024;39:689-97 PMCID:PMC10988100