Early-Life Exposures and Early-Onset Uterine Leiomyomata in Black Women in the Sister Study

Background: Uterine leiomyomata (fibroids) are hormonally responsive tumors, but little is known about risk factors. Early-life exposures may influence uterine development and subsequent response to hormones in adulthood. An earlier analysis of non-Hispanic white women who participated in the Sister Study found associations between several early-life factors and early-onset fibroids

Validity of self-reported breast cancer characteristics in a nationwide cohort of women with a family history of breast cancer

Abstract Background Women may have incomplete understanding of a breast cancer diagnosis, leading to inaccurate reporting in epidemiological studies. However, it is not feasible to obtain consent for medical records from all women participating in a study. Therefore, it is important to determine how well self-reported breast cancer characteristics correspond with what is found in medical records, but few studies have evaluated agreement of self-reported breast cancer characteristics with abstracted medical records. Methods We calculated the positive predictive value (PPV) of self-reports compared to medical records and explored whether participant characteristics may have influenced reporting accuracy. We analyzed data from 2518 reported breast cancer cases from the Sister Study, a large nationwide cohort of women with a family history of breast cancer. Results Medical records or pathology reports were obtained for 2066 of 2518 (82%) women who reported incident breast cancer. Breast cancer was confirmed for over 99% (n = 2054) of women with medical records. Confirmation rates were high for invasive, ductal, hormone receptor positive, and HER2 negative breast cancers, with little variation by race/ethnicity or age. Self-reported in situ breast cancer had a lower PPV (64.2%), with medical records showing invasive breast cancer instead, especially for older and Hispanic women. Hormone receptor (ER and PR) negative and HER2 positive self-reports had lower PPVs (83.0%, 71.6%, and 66.1% respectively). Hispanic women and women ages 65 or older at diagnosis were less able to accurately report breast cancer stage, excluding stage I. Conclusions Accuracy of reporting overall breast cancer and common subtypes is high. Despite having a family history of breast cancer and voluntarily enrolling in a study evaluating breast cancer risk factors, participants may have greater difficulty distinguishing between in situ and invasive breast cancer and may less accurately report other less common subtypes. Discrepancies may reflect women’s poor understanding of information conveyed by health care providers or lack of consistent terminology used to describe subtypes

Exome genotyping arrays to identify rare and low frequency variants associated with epithelial ovarian cancer risk

Rare and low frequency variants are not well covered in most germline genotyping arrays and are understudied in relation to epithelial ovarian cancer (EOC) risk. To address this gap, we used genotyping arrays targeting rarer protein-coding variation in 8,165 EOC cases and 11,619 controls from the international Ovarian Cancer Association Consortium (OCAC). Pooled association analyses were conducted at the variant and gene level for 98,543 variants directly genotyped through two exome genotyping projects. Only common variants that represent or are in strong linkage disequilibrium (LD) with previously-identified signals at established loci reached traditional thresholds for exome-wide significance (P < 5.0 × 10 (−) (7)). One of the most significant signals (P(all histologies )=( )1.01 × 10 (−) (13);P(serous )=( )3.54 × 10 (−) (14)) occurred at 3q25.31 for rs62273959, a missense variant mapping to the LEKR1 gene that is in LD (r(2 )=( )0.90) with a previously identified ‘best hit’ (rs7651446) mapping to an intron of TIPARP. Suggestive associations (5.0 × 10 (−) (5 )>( )P≥5.0 ×10 (−) (7)) were detected for rare and low-frequency variants at 16 novel loci. Four rare missense variants were identified (ACTBL2 rs73757391 (5q11.2), BTD rs200337373 (3p25.1), KRT13 rs150321809 (17q21.2) and MC2R rs104894658 (18p11.21)), but only MC2R rs104894668 had a large effect size (OR = 9.66). Genes most strongly associated with EOC risk included ACTBL2 (P(AML )=( )3.23 × 10 (−) (5); P(SKAT-o )=( )9.23 × 10 (−) (4)) and KRT13 (P(AML )=( )1.67 × 10 (−) (4); P(SKAT-o )=( )1.07 × 10 (−) (5)), reaffirming variant-level analysis. In summary, this large study identified several rare and low-frequency variants and genes that may contribute to EOC susceptibility, albeit with possible small effects. Future studies that integrate epidemiology, sequencing, and functional assays are needed to further unravel the unexplained heritability and biology of this disease

Validity of self-reported breast cancer characteristics in a nationwide cohort of women with a family history of breast cancer

Abstract Background Women may have incomplete understanding of a breast cancer diagnosis, leading to inaccurate reporting in epidemiological studies. However, it is not feasible to obtain consent for medical records from all women participating in a study. Therefore, it is important to determine how well self-reported breast cancer characteristics correspond with what is found in medical records, but few studies have evaluated agreement of self-reported breast cancer characteristics with abstracted medical records. Methods We calculated the positive predictive value (PPV) of self-reports compared to medical records and explored whether participant characteristics may have influenced reporting accuracy. We analyzed data from 2518 reported breast cancer cases from the Sister Study, a large nationwide cohort of women with a family history of breast cancer. Results Medical records or pathology reports were obtained for 2066 of 2518 (82%) women who reported incident breast cancer. Breast cancer was confirmed for over 99% (n = 2054) of women with medical records. Confirmation rates were high for invasive, ductal, hormone receptor positive, and HER2 negative breast cancers, with little variation by race/ethnicity or age. Self-reported in situ breast cancer had a lower PPV (64.2%), with medical records showing invasive breast cancer instead, especially for older and Hispanic women. Hormone receptor (ER and PR) negative and HER2 positive self-reports had lower PPVs (83.0%, 71.6%, and 66.1% respectively). Hispanic women and women ages 65 or older at diagnosis were less able to accurately report breast cancer stage, excluding stage I. Conclusions Accuracy of reporting overall breast cancer and common subtypes is high. Despite having a family history of breast cancer and voluntarily enrolling in a study evaluating breast cancer risk factors, participants may have greater difficulty distinguishing between in situ and invasive breast cancer and may less accurately report other less common subtypes. Discrepancies may reflect women’s poor understanding of information conveyed by health care providers or lack of consistent terminology used to describe subtypes

Manhattan plot.

<p>Log₁₀ transformed DES association p-values for individual CpGs are plotted in relation to their chromosome location. No CpGs reached genome wide significance.</p

Baseline characteristics of DES-exposed and unexposed women selected from the Sister Study.

<p>^aAge at menopause was ascertained among the 45 exposed and 45 unexposed women who were postmenopausal</p><p>^bHRT was ascertained among postmenopausal women only</p><p>^cColumn % does not add to 100% due to missing data</p><p>^dBased on Chi-Square test</p><p>Baseline characteristics of DES-exposed and unexposed women selected from the Sister Study.</p

Distribution of CpGs in the 5’end of 9 genes associated with differential methylation in animal models exposed to DES.

<p>All CpGs are ordered from 5’ to 3’. Y axis shows the difference in mean beta values of exposed and unexposed women. Circle color depicts methylation status of individual CpGs (Black = Hyper-methylated [≥70%], Grey = Semi-methylated [<70%>30%], White = Hypo-methylated [≤30%]). All sites were selected based on annotations from the Illumina manifest. A) Genes that are up regulated in mice exposed to DES. B) Genes that are down regulated in mice exposed to DES.</p