Asian Americans and Infertility: Genetic Susceptibilities, Sociocultural Stigma and Access to Care

Infertility: Disparities and Access to Services: ACOG Committee Statement No. 14

Diagnostic testing and treatment for infertility should be available to everyone in need of these services. The disparities in rates of infertility and the barriers to accessing assisted reproductive technology services should be understood through and addressed within a reproductive justice framework. Obstetrician-gynecologists and other health care professionals should identify specific populations at risk and their accompanying barriers to access to help improve infertility care across populations. Health care professionals should ask appropriate questions about social and structural drivers of health that may influence a patient's health and use of the health care system to better understand their patients' needs and lived experiences. Obstetrician-gynecologists and other health care professionals should advocate for insurance coverage for infertility services, including assisted reproductive technology; policy changes that promote comprehensive reproductive health; and evidence-based, lower cost treatment options.

EVALUATING THE RELATIONSHIPS BETWEEN GENETIC ANCESTRY AND THE CLINICAL PHENOME

There is a desire in research to move away from the concept of race as a clinical factor because it is a societal construct used as an imprecise proxy for geographic ancestry. In this study, we leverage the biobank from Vanderbilt University Medical Center, BioVU, to investigate relationships between genetic ancestry proportion and the clinical phenome. For all samples in BioVU, we calculated six ancestry proportions based on 1000 Genomes references: eastern African (EAFR), western African (WAFR), northern European (NEUR), southern European (SEUR), eastern Asian (EAS), and southern Asian (SAS). From PheWAS, we found phecode categories significantly enriched neoplasms for EAFR, WAFR, and SEUR, and pregnancy complication in SEUR, NEUR, SAS, and EAS (p < 0.003). We then selected phenotypes hypertension (HTN) and atrial fibrillation (AFib) to further investigate the relationships between these phenotypes and EAFR, WAFR, SEUR, and NEUR using logistic regression modeling and non-linear restricted cubic spline modeling (RCS). For EAS and SAS, we chose renal failure (RF) for further modeling. The relationships between HTN and AFib and the ancestries EAFR, WAFR, and SEUR were best fit by the linear model (beta p < 1x10-4 for all) while the relationships with NEUR were best fit with RCS (HTN ANOVA p = 0.001, AFib ANOVA p < 1x10-4). For RF, the relationship with SAS was best fit with a linear model (beta p < 1x10-4) while RCS model was a better fit for EAS (ANOVA p < 1x10-4). In this study, we identify relationships between genetic ancestry and phenotypes that are best fit with non-linear modeling techniques. The assumption of linearity for regression modeling is integral for proper fitting of a model and there is no knowing a priori to modeling if the relationship is truly linear.

Exposure to perfluoroalkyl substances and women's fertility outcomes in a Singaporean population-based preconception cohort

OBJECTIVES

Experimental models have demonstrated a link between exposure to perfluoroalkyl substances (PFAS) and decreased fertility and fecundability; however, human studies are scarce. We assessed the associations between preconception plasma PFAS concentrations and fertility outcomes in women.

METHODS

In a case-control study nested within the population-based Singapore Preconception Study of Long-Term Maternal and Child Outcomes (S-PRESTO), we measured PFAS in plasma collected in 2015-2017 from 382 women of reproductive age trying to conceive. Using Cox proportional hazards regression (fecundability ratios [FRs]) and logistic regression (odds ratios [ORs]) models, we assessed the associations of individual PFAS with time-to-pregnancy (TTP), and the likelihoods of clinical pregnancy and live birth, respectively, over one year of follow-up, adjusting for analytical batch, age, education, ethnicity, and parity. We used Bayesian weighted quantile sum (BWQS) regression to assess the associations of the PFAS mixture with fertility outcomes.

RESULTS

We found a 5-10 % reduction in fecundability per quartile increase of exposure to individual PFAS (FRs [95 % CIs] for clinical pregnancy = 0.90 [0.82, 0.98] for PFDA; 0.88 [0.79, 0.99] for PFOS; 0.95 [0.86, 1.06] for PFOA; 0.92 [0.84, 1.00] for PFHpA). We observed similar decreased odds of clinical pregnancy (ORs [95 % CIs] = 0.74 [0.56, 0.98] for PFDA; 0.76 [0.53, 1.09] for PFOS; 0.83 [0.59, 1.17] for PFOA; 0.92 [0.70, 1.22] for PFHpA) and live birth per quartile increases of individual PFAS and the PFAS mixture (ORs [95 % CIs] = 0.61 [0.37, 1.02] for clinical pregnancy, and 0.66 [0.40, 1.07] for live birth). Within the PFAS mixture, PFDA followed by PFOS, PFOA, and PFHpA were the biggest contributors to these associations. We found no evidence of association for PFHxS, PFNA, and PFHpS and the fertility outcomes examined.

CONCLUSIONS

Higher PFAS exposures may be associated with decreased fertility in women. The potential impact of ubiquitous PFAS exposures on infertility mechanisms requires further investigation.