STUDY QUESTION Is the increased future cardiovascular risk seen in women with endometriosis or polycystic ovary syndrome (PCOS) mitigated by functional insulin-like growth factor-1 receptor (IGF1R) single-nucleotide polymorphism (SNP) rs2016347 as previously shown in women with hypertensive disorders of pregnancy? SUMMARY ANSWER This cohort study found that women with endometriosis or PCOS who carry a T allele of IGF1R SNP rs2016347 had a reduced future risk of developing cardiovascular disease (CVD) and associated risk factors, with risk reduction dependent on cohort era. WHAT IS KNOWN ALREADY Women with endometriosis or PCOS have been shown to have an increased future risk of CVD and associated risk factors with limited predictive ability. STUDY DESIGN, SIZE, DURATION This retrospective cohort study took place in the Nurses’ Health Study 2 (NHS2), which enrolled 116 430 participants in 1989 who were followed through 2015. The study population was analyzed in its entirety, and subdivided into entry (pre-1989) and after entry (post-1989) exposure cohorts. All NHS2 participants were eligible for inclusion in the study, 9599 (8.2%) were excluded for missing covariates. PARTICIPANTS/MATERIALS, SETTING, METHODS The NHS2 enrolled female registered nurses from 14 different states who ranged in age from 25 to 42 years at study entry. Data were collected from entry and biennial questionnaires, and analysis conducted from November 2020 to June 2021. Cox proportional hazard models were used to assess risk of CVD, hypertension (HTN), hypercholesterolemia (HC) and type 2 diabetes, both with and without genotyping for rs2016347. MAIN RESULTS AND THE ROLE OF CHANCE While women without endometriosis or PCOS, as a whole, demonstrated no impact of genotype on risk in either cohort, women with endometriosis carrying a T allele had a lower risk of CVD (hazard ratio (HR), 0.48; 95% CI, 0.27–0.86, P = 0.02) and HTN (HR, 0.80; 95% CI, 0.66–0.97, P = 0.03) in the pre-1989 cohort, while those in the post-1989 cohort had a decrease in risk for HC (HR, 0.76; 95% CI, 0.62–0.94, P = 0.01). Women with PCOS in the post-1989 cohort showed a significant protective impact of the T allele on HTN (HR, 0.44; 95% CI, 0.27–0.73, P = 0.002) and HC (HR, 0.62; 95% CI, 0.40–0.95, P = 0.03). LIMITATIONS, REASONS FOR CAUTION Data on specific endometriosis lesion locations or disease stage, as well as on PCOS phenotypes were lacking. In addition, data on systemic medical treatments beyond the use of oral contraceptives were missing, and these treatments may have confounded the results. WIDER IMPLICATIONS OF THE FINDINGS These findings implicate systemic dysregulation of the insulin-like growth factor-1 axis in the development of HTN, HC and clinical CVD in endometriosis and PCOS, suggesting a common underlying pathogenetic mechanism. STUDY FUNDING/COMPETING INTEREST(S) The NHS2 infrastructure for questionnaire data collection was supported by National Institute of Health (NIH) grant U01CA176726. This work was also supported in part by NIH and National Cancer Institute grant U24CA210990; as well, research effort and publication costs were supported by the Elizabeth MA Stevens donor funds provided to the Buck Institute for Research on Aging. The authors declare they have no conflicts of interest. TRIAL REGISTRATION NUMBER N/A.
Comprehensive data on transmission mitigation behaviors and SARS-CoV-2 infection and serostatus are needed from large, community-based cohorts to identify SARS-CoV-2 risk factors and impact of public health measures. From July 2020 to March 2021, ≈5,500 adults from the East Bay Area, California were followed over three data collection rounds. We estimated the prevalence of antibodies from SARS-CoV-2 infection and COVID-19 vaccination, and self-reported COVID-19 test positivity. Population-adjusted SARS-CoV-2 seroprevalence was low, increasing from 1.03% (95% CI: 0.50-1.96) in Round 1 (July-September 2020), to 1.37% (95% CI: 0.75-2.39) in Round 2 (October-December 2020), to 2.18% (95% CI: 1.48-3.17) in Round 3 (February-March 2021). Population-adjusted seroprevalence of COVID-19 vaccination was 21.64% (95% CI: 19.20-24.34) in Round 3. Despite >99% of participants reporting wearing masks, non-Whites, lower-income, and lower-educated individuals had the highest SARS-CoV-2 seroprevalence and lowest vaccination seroprevalence. Our results demonstrate that more effective policies are needed to address these disparities and inequities.
Comprehensive data on transmission mitigation behaviors and both SARS-CoV-2 infection and serostatus are needed from large, community-based cohorts to identify COVID-19 risk factors and the impact of public health measures. We conducted a longitudinal, population-based study in the East Bay Area of Northern California. From July 2020-March 2021, approximately 5,500 adults were recruited and followed over three data collection rounds to investigate the association between geographic and demographic characteristics and transmission mitigation behavior with SARS-CoV-2 prevalence. We estimated the populated-adjusted prevalence of antibodies from SARS-CoV-2 infection and COVID-19 vaccination, and self-reported COVID-19 test positivity. Population-adjusted SARS-CoV-2 seroprevalence was low, increasing from 1.03% (95% CI: 0.50–1.96) in Round 1 (July-September 2020), to 1.37% (95% CI: 0.75–2.39) in Round 2 (October-December 2020), to 2.18% (95% CI: 1.48–3.17) in Round 3 (February-March 2021). Population-adjusted seroprevalence of COVID-19 vaccination was 21.64% (95% CI: 19.20–24.34) in Round 3, with White individuals having 4.35% (95% CI: 0.35–8.32) higher COVID-19 vaccine seroprevalence than individuals identifying as African American or Black, American Indian or Alaskan Native, Asian, Hispanic, two or more races, or other. No evidence for an association between transmission mitigation behavior and seroprevalence was observed. Despite >99% of participants reporting wearing masks individuals identifying as African American or Black, American Indian or Alaskan Native, Asian, Hispanic, two or more races, or other, as well as those in lower-income households, and lower-educated individuals had the highest SARS-CoV-2 seroprevalence and lowest vaccination seroprevalence. Results demonstrate that more effective policies are needed to address these disparities and inequities.
SummaryBackgroundThe ability to predict future risk of cancer development in non-malignant biopsies is poor. Cellular senescence has been associated with cancer as either a barrier mechanism restricting autonomous cell proliferation or a tumor-promoting microenvironmental mechanism that secretes pro-inflammatory paracrine factors. With most work done in non-human models and the heterogenous nature of senescence the precise role of senescent cells in the development of cancer in humans is not well understood. Further, more than one million non-malignant breast biopsies are taken every year that could be a major source of risk-stratification for women.MethodsWe applied single cell deep learning senescence predictors based on nuclear morphology to histological images of 4,411 H&E-stained breast biopsies from healthy female donors. Senescence was predicted in the epithelial, stromal, and adipocyte compartments using predictor models trained on cells induced to senescence by ionizing radiation (IR), replicative exhaustion (RS), or antimycin A, Atv/R and doxorubicin (AAD) exposures. To benchmark our senescence-based prediction results we generated 5-year Gail scores, the current clinical gold standard for breast cancer risk prediction.FindingsWe found significant differences in adipocyte-specific IR and AAD senescence prediction for the 86 out of 4,411 healthy women who developed breast cancer an average 4.8 years after study entry. Risk models demonstrated that individuals in the upper median of scores for the adipocyte IR model had a higher risk (OR=1.71 [1.10-2.68], p=0.019), while the adipocyte AAD model revealed a reduced risk (OR=0.57 [0.36-0.88], p=0.013). Individuals with both adipocyte risk factors had an OR of 3.32 ([1.68-7.03], p<0.001). Alone, 5-year Gail scores yielded an OR of 2.70 ([1.22-6.54], p=0.019). When combining Gail scores with our adipocyte AAD risk model, we found that individuals with both of these risk predictors had an OR of 4.70 ([2.29-10.90], p<0.001).InterpretationAssessment of senescence with deep learning allows considerable prediction of future cancer risk from non-malignant breast biopsies, something that was previously impossible to do. Furthermore, our results suggest an important role for microscope image-based deep learning models in predicting future cancer development. Such models could be incorporated into current breast cancer risk assessment and screening protocols.FundingThis study was funded by the Novo Nordisk Foundation (#NNF17OC0027812), and by the National Institutes of Health (NIH) Common Fund SenNet program (U54AG075932).
PurposePreeclampsia has been inconsistently associated with altered later-life risk of cancer. This study utilizes the Nurses’ Health Study 2 to determine if the future risk of breast and non-breast cancers in women who experience preeclampsia is modified by carrying a protective variant of rs2016347, a functional insulin-like growth factor receptor-1 (IGF1R) single nucleotide polymorphism. MethodsThis retrospective cohort study enrolled participants in 1989 and followed them through 2015, with a study population of 86,751 after exclusions. Cox proportional hazards models both with and without the impact of rs2016347 genotype were used to assess the risk of all breast cancer, hormone receptor-positive (HR+) breast cancer, and non-breast cancers. ResultsWomen with preeclampsia had no change in risk of all breast, HR+ breast, or non-breast cancers when not considering genotype. However, women carrying at least one T allele of rs2016347 had a lower risk of HR+ breast cancer, HR = 0.67, 95% CI: 0.47-0.97, P = 0.04, with interaction term P = 0.06. For non-breast cancers as a group, women carrying a T allele had an HR = 0.76, 95% CI: 0.53-1.08, P = 0.12, with interaction term P = 0.26. ConclusionsThis retrospective cohort study found that women with preeclampsia who carry a T allele of IGF1R rs2016347 had a reduced future risk of developing HR+ breast cancer, and a reduced but not statistically significant decreased risk of non-breast cancers suggesting a possible role for the IGF-1 axis in the development of cancer in these women.
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