Many epidemiologic studies of environmental exposures and disease susceptibility measure DNA methylation in white blood cells (WBC). Some studies are also starting to use saliva DNA as it is usually more readily available in large epidemiologic studies. However, little is known about the correlation of methylation between WBC and saliva DNA. We examined DNA methylation in three repetitive elements, Sat2, Alu, and LINE-1, and in four CpG sites, including AHRR (cg23576855, cg05575921), cg05951221 at 2q37.1, and cg11924019 at CYP1A1, in 57 girls aged 6-15 years with blood and saliva collected on the same day. We measured all DNA methylation markers by bisulfite-pyrosequencing, except for Sat2 and Alu, which were measured by the MethyLight assay. Methylation levels measured in saliva DNA were lower than those in WBC DNA, with differences ranging from 2.8% for Alu to 14.1% for cg05575921. Methylation levels for the three repetitive elements measured in saliva DNA were all positively correlated with those in WBC DNA. However, there was a wide range in the Spearman correlations, with the smallest correlation found for Alu (0.24) and the strongest correlation found for LINE-1 (0.73). Spearman correlations for cg05575921, cg05951221, and cg11924019 were 0.33, 0.42, and 0.79, respectively. If these findings are replicated in larger studies, they suggest that, for selected methylation markers (e.g., LINE-1), methylation levels may be highly correlated between blood and saliva, while for others methylation markers, the levels may be more tissue specific. Thus, in studies that differ by DNA source, each interrogated site should be separately examined in order to evaluate the correlation in DNA methylation levels across DNA sources.

Many epidemiologic studies of environmental exposures and disease susceptibility measure DNA methylation in white blood cells (WBC). Some studies are also starting to use saliva DNA as it is usually more readily available in large epidemiologic studies. However, little is known about the correlation of methylation between WBC and saliva DNA. We examined DNA methylation in three repetitive elements, Sat2, Alu, and LINE-1, and in four CpG sites, including AHRR (cg23576855, cg05575921), cg05951221 at 2q37.1, and cg11924019 at CYP1A1, in 57 girls aged 6-15 years with blood and saliva collected on the same day. We measured all DNA methylation markers by bisulfite-pyrosequencing, except for Sat2 and Alu, which were measured by the MethyLight assay. Methylation levels measured in saliva DNA were lower than those in WBC DNA, with differences ranging from 2.8% for Alu to 14.1% for cg05575921. Methylation levels for the three repetitive elements measured in saliva DNA were all positively correlated with those in WBC DNA. However, there was a wide range in the Spearman correlations, with the smallest correlation found for Alu (0.24) and the strongest correlation found for LINE-1 (0.73). Spearman correlations for cg05575921, cg05951221, and cg11924019 were 0.33, 0.42, and 0.79, respectively. If these findings are replicated in larger studies, they suggest that, for selected methylation markers (e.g., LINE-1), methylation levels may be highly correlated between blood and saliva, while for others methylation markers, the levels may be more tissue specific. Thus, in studies that differ by DNA source, each interrogated site should be separately examined in order to evaluate the correlation in DNA methylation levels across DNA sources.

Background

Most epidemiologic studies of puberty have only 1 source of pubertal development information (maternal, self or clinical). Interpretation of results across studies requires data on reliability and validity across sources.

Methods

The LEGACY Girls Study, a 5-site prospective study of girls aged 6 to 13 years (n = 1040) collected information on breast and pubic hair development from mothers (for all daughters) and daughters (if ≥10 years) according to Tanner stage (T1-5) drawings. At 2 LEGACY sites, girls (n = 282) were also examined in the clinic by trained professionals. We assessed agreement (κ) and validity (sensitivity and specificity) with the clinical assessment (gold standard) for both the mothers' and daughters' assessment in the subcohort of 282. In the entire cohort, we examined the agreement between mothers and daughters.

Results

Compared with clinical assessment, sensitivity of maternal assessment for breast development was 77.2 and specificity was 94.3. In girls aged ≥11 years, self-assessment had higher sensitivity and specificity than maternal report. Specificity for both mothers and self, but not sensitivity, was significantly lower for overweight girls. In the overall cohort, maternal and daughter agreement for breast development and pubic hair development (T2+ vs T1) were similar (0.66, [95% confidence interval 0.58-0.75] and 0.69 [95% confidence interval 0.61-0.77], respectively), but declined with age. Mothers were more likely to report a lower Tanner stage for both breast and pubic hair compared with self-assessments.

Conclusions

These differences in validity should be considered in studies measuring pubertal changes longitudinally when they do not have access to clinical assessments.

Purpose

Researchers must monitor the safety of research participants, particularly in studies involving children and adolescents. Yet, there is limited guidance for the development and implementation of oversight committees for psychosocial, behavioral intervention, and observational studies.

Methods

We implemented a model for an Event Monitoring Committee (EMC) in three related studies recruiting 6- to 19-year-old girls from families with and without breast cancer.

Results

The EMC model can be valuable for investigators and local institutional review boards when additional oversight is desired. Recommendations are provided and intended to be broadly applicable to a wide range of research activities designed to improve the health of children, adolescents, and families. EMC goals, membership, and procedures for monitoring and assessing risks and benefits should be defined but should also be flexible and tailored to the study design and population. The EMC model also provides an independent comprehensive, study-wide oversight mechanism for multicenter psychosocial, behavioral intervention, and observational studies.

Conclusions

An EMC provides an alternative oversight approach where additional independent assessment and oversight of study-related risks are desired, particularly in the setting of vulnerable populations, children and adolescents, or where risks nontraditional to the medical field (i.e., social, emotional, or cultural) are possible.

Background

Pubertal milestones, such as onset of breast development and menstruation, play an important role in breast cancer etiology. It is unclear if these milestones are different in girls with a first- or second-degree breast cancer family history (BCFH).

Methods

In the LEGACY Girls Study (n = 1040), we examined whether three mother/guardian-reported pubertal milestones (having reached Tanner Stage 2 or higher (T2+) for breast and pubic hair development, and having started menstruation) differed by BCFH. We also examined whether associations between body size and race/ethnicity and pubertal milestones were modified by BCFH. We used mother/guardian reports as the primary measure of pubertal milestones, but also conducted sensitivity analyses using clinical Tanner measurements available for a subcohort (n = 204). We analyzed cross-sectional baseline data with logistic regression models for the entire cohort, and longitudinal data with Weibull survival models for the subcohort of girls that were aged 5-7 years at baseline (n = 258).

Results

BCFH was modestly, but not statistically significantly, associated with Breast T2+ (odds ratio (OR) = 1.36, 95% confidence interval (CI) = 0.88-2.10), with a stronger association seen in the subcohort of girls with clinical breast Tanner staging (OR = 2.20, 95% CI = 0.91-5.32). In a longitudinal analysis of girls who were aged 5-7 years at baseline, BCFH was associated with a 50% increased rate of having early breast development (hazard ratio (HR) = 1.49, 95% CI = 1.0-2.21). This association increased to twofold in girls who were not overweight at baseline (HR = 2.04, 95% CI = 1.29-3.21). BCFH was not associated with pubic hair development and post-menarche status. The median interval between onset of breast development and menarche was longer for BCFH+ than BCFH- girls (2.3 versus 1.7 years), suggesting a slower developmental tempo for BCFH+ girls. Associations between pubertal milestones and body size and race/ethnicity were similar in girls with or without a BCFH. For example, weight was positively associated with Breast T2+ in both girls with (OR = 1.06 per 1 kg, 95% CI = 1.03-1.10) and without (OR = 1.14 per 1 kg, 95% CI = 1.04-1.24) a BCFH.

Conclusions

These results suggest that BCFH may be related to earlier breast development and slower pubertal tempo independent of body size and race/ethnicity.

Purpose

Researchers must monitor the safety of research participants, particularly in studies involving children and adolescents. Yet, there is limited guidance for the development and implementation of oversight committees for psychosocial, behavioral intervention, and observational studies.

Methods

We implemented a model for an Event Monitoring Committee (EMC) in three related studies recruiting 6- to 19-year-old girls from families with and without breast cancer.

Results

The EMC model can be valuable for investigators and local institutional review boards when additional oversight is desired. Recommendations are provided and intended to be broadly applicable to a wide range of research activities designed to improve the health of children, adolescents, and families. EMC goals, membership, and procedures for monitoring and assessing risks and benefits should be defined but should also be flexible and tailored to the study design and population. The EMC model also provides an independent comprehensive, study-wide oversight mechanism for multicenter psychosocial, behavioral intervention, and observational studies.

Conclusions

An EMC provides an alternative oversight approach where additional independent assessment and oversight of study-related risks are desired, particularly in the setting of vulnerable populations, children and adolescents, or where risks nontraditional to the medical field (i.e., social, emotional, or cultural) are possible.

Background

Although the timing of pubertal milestones has been associated with breast cancer risk, few studies of girls' development include girls at increased breast cancer risk due to their family history.

Methods

The Lessons in Epidemiology and Genetics of Adult Cancer from Youth (LEGACY) Girls Study was initiated in 2011 in the USA and Canada to assess the relation between early life exposures and intermediate markers of breast cancer risk (e.g., pubertal development, breast tissue characteristics) and to investigate psychosocial well being and health behaviors in the context of family history. We describe the methods used to establish and follow a cohort of 1,040 girls ages 6-13 years at baseline, half with a breast cancer family history, and the collection of questionnaire data (family history, early life exposures, growth and development, psychosocial and behavioral), anthropometry, biospecimens, and breast tissue characteristics using optical spectroscopy.

Results

During this initial 5-year phase of the study, follow-up visits are conducted every 6 months for repeated data and biospecimen collection. Participation in baseline components was high (98% for urine, 97.5% for blood or saliva, and 98% for anthropometry). At enrollment, 77% of girls were premenarcheal and 49% were at breast Tanner stage T1.

Conclusions

This study design allows thorough examination of events affecting girls' growth and development and how they differ across the spectrum of breast cancer risk. A better understanding of early life breast cancer risk factors will be essential to enhance prevention across the lifespan for those with and without a family history of the disease.

Introduction

The etiology of familial breast cancer is complex and involves genetic and environmental factors such as hormonal and lifestyle factors. Understanding familial aggregation is a key to understanding the causes of breast cancer and to facilitating the development of effective prevention and therapy. To address urgent research questions and to expedite the translation of research results to the clinical setting, the National Cancer Institute (USA) supported in 1995 the establishment of a novel research infrastructure, the Breast Cancer Family Registry, a collaboration of six academic and research institutions and their medical affiliates in the USA, Canada, and Australia.

Methods

The sites have developed core family history and epidemiology questionnaires, data dictionaries, and common protocols for biospecimen collection and processing and pathology review. An Informatics Center has been established to collate, manage, and distribute core data.

Results

As of September 2003, 9116 population-based and 2834 clinic-based families have been enrolled, including 2346 families from minority populations. Epidemiology questionnaire data are available for 6779 affected probands (with a personal history of breast cancer), 4116 unaffected probands, and 16,526 relatives with or without a personal history of breast or ovarian cancer. The biospecimen repository contains blood or mouthwash samples for 6316 affected probands, 2966 unaffected probands, and 10,763 relatives, and tumor tissue samples for 4293 individuals.

Conclusion

This resource is available to internal and external researchers for collaborative, interdisciplinary, and translational studies of the genetic epidemiology of breast cancer. Detailed information can be found at the URL http://www.cfr.epi.uci.edu/.

Family history, a well-established risk factor for breast cancer, can have both genetic and environmental contributions. Shared environment in families as well as epigenetic changes that also may be influenced by shared genetics and environment may also explain familial clustering of cancers. Epigenetic regulation, such as DNA methylation, can change the activity of a DNA segment without a change in the sequence; environmental exposures experienced across the life course can induce such changes. However, genetic-epigenetic interactions, detected as methylation quantitative trait loci (mQTLs; a.k.a. meQTLs) and haplotype-dependent allele-specific methylation (hap-ASM), can also contribute to inter-individual differences in DNA methylation patterns. To identify differentially methylated regions (DMRs) associated with breast cancer susceptibility, we examined differences in white blood cell DNA methylation in 29 candidate genes in 426 girls (ages 6-13 years) from the LEGACY Girls Study, 239 with and 187 without a breast cancer family history (BCFH). We measured methylation by targeted massively parallel bisulfite sequencing (bis-seq) and observed BCFH DMRs in two genes: ESR1 (Δ4.9%, P = 0.003) and SEC16B (Δ3.6%, P = 0.026), each of which has been previously implicated in breast cancer susceptibility and pubertal development. These DMRs showed high inter-individual variability in methylation, suggesting the presence of mQTLs/hap-ASM. Using single nucleotide polymorphisms data in the bis-seq amplicon, we found strong hap-ASM in SEC16B (with allele specific-differences ranging from 42% to 74%). These findings suggest that differential methylation in genes relevant to breast cancer susceptibility may be present early in life, and that inherited genetic factors underlie some of these epigenetic differences.

Objective

Understanding how young girls respond to growing up with breast cancer family histories is critical given expansion of genetic testing and breast cancer messaging. We examined the impact of breast cancer family history on psychosocial adjustment and health behaviors among >800 girls in the multicenter LEGACY Girls Study.

Methods

Girls aged 6 to 13 years with a family history of breast cancer or familial BRCA1/2 mutation (BCFH+), peers without a family history (BCFH-), and their biological mothers completed assessments of psychosocial adjustment (maternal report for 6- to 13-year-olds, self-report for 10- to 13-year-olds), breast cancer-specific distress, perceived risk of breast cancer, and health behaviors (10- to 13-year-olds).

Results

BCFH+ girls had better general psychosocial adjustment than BCFH- peers by maternal report. Psychosocial adjustment and health behaviors did not differ significantly by self-report among 10- to 13-year-old girls. BCFH+ girls reported higher breast cancer-specific distress (P = .001) and were more likely to report themselves at increased breast cancer risk than BCFH- peers (38.4% vs 13.7%, P < .001), although many girls were unsure of their risk. In multivariable analyses, higher daughter anxiety was associated with higher maternal anxiety and poorer family communication. Higher daughter breast cancer-specific distress was associated with higher maternal breast cancer-specific distress.

Conclusions

Although growing up in a family at risk for breast cancer does not negatively affect general psychosocial adjustment among preadolescent girls, those from breast cancer risk families experience greater breast cancer-specific distress. Interventions to address daughter and mother breast cancer concerns and responses to genetic or familial risk might improve psychosocial outcomes of teen daughters.