PubMed Health⌕ Search
Home/Archive/PubMed

PubMed · 38821016

Phthalates and sex steroid hormones across the perimenopausal period: A longitudinal analysis of the Midlife Women's Health Study.

Ryan S Babadi·Paige L Williams·Emma V Preston·Zhong Li·Rebecca L Smith·Rita S Strakovsky·Shruthi Mahalingaiah·Russ Hauser·Jodi A Flaws·Tamarra James-Todd
View original source ↗Export metadata ↓

Abstract

BACKGROUND: The menopausal transition involves significant sex hormone changes. Environmental chemicals, such as urinary phthalate metabolites, are associated with sex hormone levels in cross-sectional studies. Few studies have assessed longitudinal associations between urinary phthalate metabolite concentrations and sex hormone levels during menopausal transition. METHODS: Pre- and perimenopausal women from the Midlife Women's Health Study (MWHS) (n = 751) contributed data at up to 4 annual study visits. We quantified 9 individual urinary phthalate metabolites and 5 summary measures (e.g., phthalates in plastics (∑Plastic)), using pooled annual urine samples. We measured serum estradiol, testosterone, and progesterone collected at each study visit, unrelated to menstrual cycling. Linear mixed-effects models and hierarchical Bayesian kernel machine regression analyses evaluated adjusted associations between individual and phthalate mixtures with sex steroid hormones longitudinally. RESULTS: We observed associations between increased concentrations of certain phthalate metabolites and lower testosterone and higher sub-ovulatory progesterone levels, e.g., doubling of monoethyl phthalate (MEP), monobenzyl phthalate (MBzP), di-2-ethylhexyl phthalate (∑DEHP) metabolites, ∑Plastic, and ∑Phthalates concentrations were associated with lower testosterone (e.g., for ∑DEHP: -4.51%; 95% CI: -6.72%, -2.26%). For each doubling of MEP, certain DEHP metabolites, and summary measures, we observed higher mean sub-ovulatory progesterone (e.g., ∑AA (metabolites with anti-androgenic activity): 6.88%; 95% CI: 1.94%, 12.1%). Higher levels of the overall time-varying phthalate mixture were associated with lower estradiol and higher progesterone levels, especially for 2nd year exposures. CONCLUSIONS: Phthalates were longitudinally associated with sex hormone levels during the menopausal transition. Future research should assess such associations and potential health impacts during this understudied period.

Explore related subjects

HumansPhthalic AcidsFemaleMiddle AgedLongitudinal StudiesPerimenopauseEnvironmental PollutantsEstradiolAdultGonadal Steroid HormonesProgesteroneEnvironmental ExposureWomen's HealthTestosteroneEndocrine disrupting chemicalsHormonesMenopauseMidlifePhthalatesWomenJournal Article

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Ryan S Babadi, Paige L Williams, Emma V Preston, Zhong Li, Rebecca L Smith, Rita S Strakovsky, Shruthi Mahalingaiah, Russ Hauser, Jodi A Flaws, Tamarra James-Todd. 2024-05-23. Phthalates and sex steroid hormones across the perimenopausal period: A longitudinal analysis of the Midlife Women's Health Study.. https://doi.org/10.1016/j.envint.2024.108770

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2027

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans↗
PubMed2027

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans↗
PubMed2027

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans↗