Jane S Burns1, Oleg Sergeyev2, Mary M Lee3, Paige L Williams4, Lidia Mínguez-Alarcón5, Bora Plaku-Alakbarova6, Sergey Sokolov7, Sergey Kovalev7, Holger M Koch8, Albert T Lebedev7, Russ Hauser9, Susan A Korrick5. 1. Environmental and Occupational Medicine and Epidemiology Program, Department of Environmental Health, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Building 1, Boston, MA, 02115, USA. Electronic address: jburns@hsph.harvard.edu. 2. Group of Epigenetic Epidemiology, Belozersky Research Institute of Physico-Chemical Biology, Lomonosov Moscow State University, Leninskye Gory, House 1, Building 40, Room 322, 119992, Moscow, Russia; Chapaevsk Medical Association, Meditsinskaya Str., 3a, Chapaevsk, Samara Region, 446100, Russia. 3. Nemours Children's Health, 1600 Rockland Road, Wilmington, 19803, USA; Department of Pediatrics, Sidney Kimmel Medical School, Jefferson University, Philadelphia, PA, USA. 4. Department of Biostatistics, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Building 2, Room 443, Boston, MA, 02115, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave., Kresge Building, 9th Floor, Boston, MA, 02115, USA. 5. Environmental and Occupational Medicine and Epidemiology Program, Department of Environmental Health, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Building 1, Boston, MA, 02115, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 401 Park Drive, 3rd Floor West, Boston, MA, 02215, USA. 6. Environmental and Occupational Medicine and Epidemiology Program, Department of Environmental Health, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Building 1, Boston, MA, 02115, USA; Epidemiology Division, Optuminsight Life Sciences, Boston, MA, USA. 7. Chemistry Department, Lomonosov Moscow State University, Moscow, 119991, Leninskie Gory 1/3, Russian Federation. 8. Institute for Prevention and Occupational Medicine of the German Social Accident Insurance - Institute of the Ruhr University Bochum (IPA), Bürkle-de-la-Camp-Platz 1, 44789, Bochum, Germany. 9. Environmental and Occupational Medicine and Epidemiology Program, Department of Environmental Health, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Building 1, Boston, MA, 02115, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave., Kresge Building, 9th Floor, Boston, MA, 02115, USA.
Abstract
BACKGROUND: Although phthalate exposures have been associated with adverse effects on male reproductive health, few studies have explored longitudinal associations with male pubertal development. OBJECTIVES: We examined the association of prepubertal urinary concentrations of phthalate metabolites with age at pubertal onset in a prospective cohort of Russian boys. METHODS: At enrollment at ages 8-9 years, medical history, dietary, and demographic information was collected. At entry and annually, physical examinations and pubertal staging [Genitalia (G), Pubarche (P), and testicular volume (TV, in ml)] were conducted and spot urines were collected. Prepubertal urine samples (defined as either TV = 1, 2 and G = 1, 2 or TV = 3 and G = 1) were pooled for each boy and phthalate metabolite concentrations were quantified using isotope dilution LC-MS/MS at Moscow State University. We measured 15 metabolites including those from anti-androgenic parent phthalates (AAPs) such as di (2-ethylhexyl) (DEHP) and di-isononyl (DiNP) phthalates as well as monobenzyl (MBzP), mono-n-butyl (MnBP), and mono-isobutyl (MiBP) metabolites. We calculated the molar sums of DEHP (∑DEHP), DiNP (∑DiNP), and AAP (∑AAP) metabolites. Separate interval-censored models were used to assess associations of quartiles of prepubertal phthalate metabolites with each pubertal onset indicator, G2+, P2+ and TV > 3 mL, adjusted for covariates and urine specific gravity. RESULTS: 304 boys had 752 prepubertal urine samples (median 2, range: 1-6) for pooling. In adjusted models, higher urinary AAPs were consistently associated with later pubertal onset (P2) with mean shifts ranging from 8.4 to 14.2 months for the highest versus lowest quartiles. Significantly later onset for G2 and TV > 3 mL was observed for higher versus lower quartiles of MiBP, MBzP, ∑DEHP and ∑DiNP. CONCLUSIONS: On average, boys with higher concentrations of prepubertal urinary AAPs had later pubertal onset by six months to over a year. The impact of AAPs on timing of male puberty may be attributable to disruption of androgen-dependent biological pathways.
BACKGROUND: Although phthalate exposures have been associated with adverse effects on male reproductive health, few studies have explored longitudinal associations with male pubertal development. OBJECTIVES: We examined the association of prepubertal urinary concentrations of phthalate metabolites with age at pubertal onset in a prospective cohort of Russian boys. METHODS: At enrollment at ages 8-9 years, medical history, dietary, and demographic information was collected. At entry and annually, physical examinations and pubertal staging [Genitalia (G), Pubarche (P), and testicular volume (TV, in ml)] were conducted and spot urines were collected. Prepubertal urine samples (defined as either TV = 1, 2 and G = 1, 2 or TV = 3 and G = 1) were pooled for each boy and phthalate metabolite concentrations were quantified using isotope dilution LC-MS/MS at Moscow State University. We measured 15 metabolites including those from anti-androgenic parent phthalates (AAPs) such as di (2-ethylhexyl) (DEHP) and di-isononyl (DiNP) phthalates as well as monobenzyl (MBzP), mono-n-butyl (MnBP), and mono-isobutyl (MiBP) metabolites. We calculated the molar sums of DEHP (∑DEHP), DiNP (∑DiNP), and AAP (∑AAP) metabolites. Separate interval-censored models were used to assess associations of quartiles of prepubertal phthalate metabolites with each pubertal onset indicator, G2+, P2+ and TV > 3 mL, adjusted for covariates and urine specific gravity. RESULTS: 304 boys had 752 prepubertal urine samples (median 2, range: 1-6) for pooling. In adjusted models, higher urinary AAPs were consistently associated with later pubertal onset (P2) with mean shifts ranging from 8.4 to 14.2 months for the highest versus lowest quartiles. Significantly later onset for G2 and TV > 3 mL was observed for higher versus lower quartiles of MiBP, MBzP, ∑DEHP and ∑DiNP. CONCLUSIONS: On average, boys with higher concentrations of prepubertal urinary AAPs had later pubertal onset by six months to over a year. The impact of AAPs on timing of male puberty may be attributable to disruption of androgen-dependent biological pathways.
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