Russ Hauser

Supplementary Figure from Association Study between Polymorphisms in DNA Methylation–Related Genes and Testicular Germ Cell Tumor Risk

Supplementary Data from Association Study between Polymorphisms in DNA Methylation–Related Genes and Testicular Germ Cell Tumor Risk

Few studies have prospectively examined the joint effect of mercury (Hg) and omega-3 long-chain polyunsaturated fatty acids on gestational weight gain (GWG). This exploratory study included 120 women from the Environment and Reproductive Health (EARTH) study with preconception measurements of hair Hg and serum eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), followed through pregnancy. Linear regression was used to examine associations between hair Hg and GWG, while logistic regression estimated the odds of inadequate GWG based on National Academy of Medicine recommendations. In unadjusted models, higher hair Hg (≥1 vs. <1 ppm) was associated with lower GWG (β = −1.89; 95% CI: −3.70, −0.08) and increased odds of insufficient GWG (OR = 2.27; 95% CI: 1.00, 5.18). However, after multivariable adjustment including serum EPA + DHA, these associations were attenuated and became non-significant. A negative, though not statistically significant, association between hair Hg and GWG was observed among women in the lowest tertile of serum EPA + DHA (≥1 vs. <1 ppm: β = −3.26; 95% CI: −7.69, 1.17), whereas no such association was observed among those in higher tertiles (β [95% CI] = 0.44 [−4.21, 5.09] and −1.05 [−4.13, 2.02], respectively). Our findings suggest that the association between preconception Hg exposure and insufficient GWG may differ by serum EPA + DHA, but results require confirmation in cohorts with larger sample sizes.

Background/Objectives: Few studies have investigated the association of dietary glycemic index (GI), glycemic load (GL), and carbohydrate intake with antral follicle count (AFC). This study aimed to investigate the association of total carbohydrate intake and carbohydrate quality, measured by dietary GI and GL, with ovarian reserve assessed by AFC. Methods: This study included 653 females from the Environment And Reproductive Health Study who completed AFC and food frequency questionnaire. Of these, 579 female individuals had a quantifiable AFC in both ovaries and were included in the primary analysis. We estimated average GI and GL for each participant from self-reported intakes of carbohydrate-containing foods and divided participants into tertiles. Poisson regression models were used to quantify the relations of GI, GL, carbohydrates, and AFC while adjusting for potential confounders. Results: Participants had a median age of 35 y. Compared to participants in the lowest tertile of dietary GI, those in the highest tertile had a 6.3% (0.6%, 12.3%) higher AFC (p, trend 0.03) after adjustment for potential confounders. Stratified analyses revealed that the association between GI and AFC was present only among participants who had not undergone infertility evaluations. Conclusions: A higher dietary GI was associated with a higher AFC. Subgroup analyses among individuals who had not had a diagnostic evaluation of infertility before joining the study suggest that high-glycemic carbohydrates may be related to PCOM.

We examined whether mixtures of urinary concentrations of bisphenol A (BPA), parabens and phthalate metabolites were associated with serum lipid levels among 175 pregnant women who enrolled in the Environment and Reproductive Health (EARTH) Study (2005–2017), including triglycerides, total cholesterol, high-density lipoprotein (HDL), non-HDL, and low-density lipoprotein (LDL). We applied Bayesian Kernel Machine Regression (BKMR) and quantile g-computation while adjusting for confounders. In the BKMR models, we found no associations between chemical mixture and lipid levels, e.g., total cholesterol [mean difference (95% CRI, credible interval) = 0.02 (−0.31, 0.34)] and LDL [mean difference (95% CRI) = 0.10 (−0.22, 0.43)], when comparing concentrations at the 75th to the 25th percentile. When stratified by BMI, we found suggestive positive relationships between urinary propylparaben and total cholesterol and LDL among women with high BMI [mean difference (95% CRI) = 0.25 (−0.26, 0.75) and 0.35 (−0.25, 0.95)], but not with low BMI [mean difference (95% CRI) = 0.00 (−0.06, 0.07) and 0.00 (−0.07, 0.07)]. No association was found by quantile g-computation. This exploratory study suggests mixtures of phenol and phthalate metabolites were not associated with serum lipid levels during pregnancy, while there were some suggestive associations for certain BMI subgroups. Larger longitudinal studies with multiple assessments of both exposure and outcome are needed to corroborate these novel findings.

BACKGROUND Wrist skin temperature is affected by hormonal changes associated with the menstrual cycle and can be used to estimate the timing of cycle events. OBJECTIVE The objective of this study was evaluation of three algorithms available on compatible models of iPhone and Apple Watch which use wrist temperature to retrospectively estimate the day of ovulation and to predict next menses start day. METHODS We conducted a prospective cohort study of menstruating females aged 14 and older who logged their menses, performed urine leutinizing hormone testing to define day of ovulation, recorded daily basal body temperature (BBT) and collected overnight wrist temperature. Algorithm performance was evaluated for three algorithms: one for retrospective ovulation day estimate in ongoing cycles (Algorithm 1), one for retrospective ovulation estimate in completed cycles (Algorithm 2), and one for prediction of next menses start day (Algorithm 3). Cycles considered to have likely tracking errors as well as those missing temperature data for 30% or more of days were excluded from analysis. Each algorithm’s performance was evaluated under multiple scenarios, including for participants with all typical cycle lengths (23-35 days) and those with some atypical cycle lengths (35 days), in cycles with the temperature change of ≥ 0.2°C typically associated with ovulation, and with any temperature change included. RESULTS Two-hundred sixty participants provided 889 cycles. Algorithm 1 provided a retrospective ovulation day estimate in 80.5% of ongoing menstrual cycles of all cycle lengths with ≥ 0.2°C wrist temperature signal with a mean absolute error (MAE) of 1.59 days (95% CI 1.45, 1.74), with 80.0% of estimates being within +/- 2 days of ovulation. Retrospective ovulation day in an ongoing cycle (Algorithm 1) was estimated in 81.9% (MAE 1.53 days, 95% CI 1.35, 1.70) of cycles for participants with all typical cycle lengths, and 77.7% (MAE 1.71 days, 95% CI 1.42, 2.01) of cycles for participants with atypical cycle lengths. Algorithm 2 provided a retrospective ovulation day estimate in 80.8% of completed menstrual cycles with ≥ 0.2°C wrist temperature signal with an MAE of 1.22 days (95% CI 1.11, 1.33), with 89.0% of estimates being within +/- 2 days of ovulation. Wrist temperature provided next menses start day prediction (Algorithm 3) at the time of ovulation estimate (89.4% within +/- 3 days of menses start) with a MAE of 1.65 (95% CI 1.52, 1.79) days in cycles with ≥ 0.2°C wrist temperature signal. CONCLUSIONS Algorithms using wrist temperature can provide retrospective ovulation estimates and next menses start day predictions for individuals with typical or atypical cycle lengths. Inclusion of wrist skin temperature, along with other physiologic measurements, can aid in menstrual cycle tracking and understanding cycle patterns. CLINICALTRIAL NCT05852951

The associations between urinary phenol concentrations and markers of thyroid function and autoimmunity among potentially susceptible subgroups, such as subfertile women, have been understudied, especially when considering chemical mixtures. We evaluated cross-sectional associations of urinary phenol concentrations, individually and as a mixture, with serum markers of thyroid function and autoimmunity. We included 339 women attending a fertility center who provided one spot urine and one blood sample at enrollment (2009–2015). We quantified four phenols in urine using isotope dilution high-performance liquid chromatography–tandem mass spectrometry, and biomarkers of thyroid function (thyroid-stimulating hormone (TSH), free and total thyroxine (fT4, TT4), and triiodothyronine (fT3, TT3)), and autoimmunity (thyroid peroxidase (TPO) and thyroglobulin (Tg) antibodies (Ab)) in serum using electrochemoluminescence assays. We fit linear and additive models to investigate the association between urinary phenols—both individually and as a mixture—and serum thyroid function and autoimmunity, adjusted for confounders. As a sensitivity analysis, we also applied Bayesian Kernel Machine Regression (BKMR) to investigate non-linear and non-additive interactions. Urinary bisphenol A was associated with thyroid function, in particular, fT₃ (mean difference for a 1 log unit increase in concentration: −0.088; 95% CI [−0.151, −0.025]) and TT₃ (−0.066; 95% CI [−0.112, −0.020]). Urinary methylparaben and triclosan were also associated with several thyroid hormones. The overall mixture was negatively associated with serum fT₃ concentrations (mean difference comparing all four mixture components at their 75th vs. 25th percentiles: −0.19, 95% CI [−0.35, −0.03]). We found no evidence of non-linearity or interactions. These results add to the current literature on phenol exposures and thyroid function in women, suggesting that some phenols may alter the thyroid system.

Background: Maternal exposure to cigarette smoke in pregnancy may play a role in the development of testicular cancer in offspring. An updated and comprehensive systematic review of the available evidence is needed. Objective: To identify and evaluate current evidence on maternal exposure to cigarette smoke during pregnancy and testicular cancer in offspring. Methods: A systematic search of English peer-reviewed original literature in PubMed through a block search approach. Publications were considered if assessing maternal exposure to cigarette smoke and the risk of testicular cancer in offspring. Results: Among the 636 identified records, 14 publications were eligible for review and 10 for meta-analysis. Quality assessment of the publications was conducted. Most included publications were case-control studies (n = 11, 79%), while the remaining were ecological studies (n = 3, 21%). Completeness of reporting was high, but more than half were considered subject to potential bias. The trend synthesis showed that half (n = 7) of the included publications demonstrated a higher risk of testicular cancer in the sons of mothers exposed to cigarette smoke during pregnancy. The meta-analysis generated an overall summary risk estimate of 1.00 (95% CI: 0.88; 1.15) (n = 10 publications), with a lower risk for seminoma (0.79, 95% CI: 0.59; 1.04) and nonseminoma (0.96, 95% CI: 0.74; 1.26) (n = 4 publications). Conclusions: This systematic review did not provide evidence of an association between maternal exposure to cigarette smoke and risk of testicular cancer in offspring. An overall positive trend was suggested, but it had low statistical precision. The methodological limitations across publications encourage further research based on valid exposure data.