Citations

Abstract Background: Terminal ductal lobular units (TDLUs), the functional units of the breast for lactation, are the structures from which most breast cancers arise. TDLU involution, reflecting atrophy and loss of TDLUs, has been related to lower subsequent breast cancer risk. The predictors of such breast tissue aging, however, are not well defined. Given that estrogens and other hormones play a central role in the etiology of postmenopausal breast cancers, we conducted a study to assess the relationship between four hormones and sex hormone-binding globulin (SHBG) with markers of TDLU involution. Methods: Subjects included healthy women who volunteered between 2009 and 2011 to participate in the Komen Tissue Bank Study. Participants completed a risk factor questionnaire, provided a blood sample, and donated breast tissue for research. Our analysis was restricted to postmenopausal women who were not currently taking menopausal hormones (n=153). A pathologist, masked to patient data, assessed tissue sections for the presence of TDLUs and, among sections containing TDLUs (n=88), measured TDLU diameters for up to ten TDLUs per section. Both presence of TDLUs and TDLU diameter are inversely related to involution. Chemiluminescent immunometric assays were used to measure serum levels of estradiol (E2), SHBG, follicle-stimulating hormone (FSH), and prolactin. Percent free E2 was calculated from measured E2 and SHBG levels. Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the presence of TDLUs (none or any) associated with tertiles of serum hormone and SHBG levels. Multivariable ordinal logistic regression was used to calculate ORs, 95% CIs, and p-trend for TDLU diameter categorized as tertiles (≥218.4, 218.4-281, and ≥281 microns) with serum hormone and SHBG levels. All models were adjusted for potential confounding factors. Results: The study population was 87.6% Caucasian with a mean age of 59.5 years, and >2/3 of the women were overweight or obese. Increasing percent free E2 was significantly associated with larger TDLU diameter (OR>2.53 vs. ≥1.99: 5.58, 95% CI: 1.48-21.07; p-trend=0.01), whereas increasing SHBG was associated with smaller TDLU diameter (OR>73nmol/L vs. ≥38 nmol/L: 0.19, 95% CI: 0.05-0.74; p-trend=0.02). Total E2 (p-trend=0.49), FSH (p-trend=0.85), and prolactin (p-trend=0.58) were not associated with TDLU diameter. We did not find significant relationships between the presence of TDLUs and any of the serum levels. Our observed relationships were not modified by age or other breast cancer risk factors, including BMI, years since menopause, and history of bilateral oophorectomy. Conclusion: Based on limited data, these findings suggest that sex hormones may play a role in TDLU involution. Thus, TDLU involution may represent one mechanism by which hormone levels influence breast cancer risk. TDLU measurements may therefore be helpful in assessing breast cancer risk as a marker of breast tissue aging. Analysis of the relationships between hormones and TDLU involution among premenopausal women may provide additional insights into early events in breast carcinogenesis. Citation Format: Zeina G. Khodr, Mark E. Sherman, Ruth M. Pfeiffer, Gretchen L. Gierach, Louise A. Brinton, Roni T. Falk, Deesha Patel, Laura Linville, Susan E. Clare, Daniel Visscher, Carolyn Mies, Stephen Hewitt, Anna Maria Storniolo, Jonine D. Figueroa. Endogenous hormone levels and lobular involution of the breast among healthy, postmenopausal women in the Komen Tissue Bank Study. [abstract]. In: Proceedings of the Eleventh Annual AACR International Conference on Frontiers in Cancer Prevention Research; 2012 Oct 16-19; Anaheim, CA. Philadelphia (PA): AACR; Cancer Prev Res 2012;5(11 Suppl):Abstract nr B89.

Abstract Background: Both shorter and longer telomeres in peripheral blood leukocyte (PBL) DNA have been associated with cancer risk. However, associations remain inconsistent across studies of the same cancer type. This study compares DNA preparation methods to determine telomere length from patients with colorectal cancer. Methods: We examined PBL relative telomere length (RTL) measured by quantitative PCR (qPCR) in 1,033 patients with colorectal cancer and 2,952 healthy controls. DNA was extracted with phenol/chloroform, PureGene, or QIAamp. Results: We observed differences in RTL depending on DNA extraction method (P < 0.001). Phenol/chloroform-extracted DNA had a mean RTL (T/S ratio) of 0.78 (range 0.01–6.54) compared with PureGene-extracted DNA (mean RTL of 0.75; range 0.00–12.33). DNA extracted by QIAamp yielded a mean RTL of 0.38 (range 0.02–3.69). We subsequently compared RTL measured by qPCR from an independent set of 20 colorectal cancer cases and 24 normal controls in PBL DNA extracted by each of the three extraction methods. The range of RTL measured by qPCR from QIAamp-extracted DNA (0.17–0.58) was less than from either PureGene or phenol/chloroform (ranges, 0.04–2.67 and 0.32–2.81, respectively). Conclusions: RTL measured by qPCR from QIAamp-extracted DNA was less than from either PureGene or phenol/chloroform (P < 0.001). Impact: Differences in DNA extraction method may contribute to the discrepancies between studies seeking to find an association between the risk of cancer or other diseases and RTL. Cancer Epidemiol Biomarkers Prev; 22(11); 2047–54. ©2013 AACR.

Abstract Background: Terminal duct lobular units (TDLUs) are the anatomical source of most breast cancers. TDLU involution, manifested as atrophy and loss of TDLUs, is associated with reduced breast cancer risk. We hypothesize that breast cancer susceptibility loci are associated with TDLU involution. Accordingly, we evaluated relationships between 25 established breast cancer susceptibility markers and their association with TDLU involution in the Susan G. Komen for the Cure® Tissue Bank (KTB). Methods: Subjects were women ages 18-84 (N=680), who had no personal history of any cancer, were not currently taking menopausal hormones, completed a risk factor questionnaire, provided an Oragene® saliva sample, and donated a 10-guage needle tissue core from the upper outer breast quadrant for research. We genotyped 25 known single nucleotide polymorphisms (SNPs) associated with breast cancer risk using TaqMan® assays. Pathologists masked to risk data classified three features inversely related to TDLU involution using one histological section of breast tissue/subject: number of TDLUs per section (TDLU density), TDLU diameters and number of acini per TDLU. SNPS were compared to metrics of TDLU involution categorized in tertiles: TDLU density (0-1, 2-8, 9+), mean TDLU diameter (53-291, 292-415, 416-1143 microns), and mean number of acini per TDLU (2-10, 11-20, 21+). We estimated age-adjusted per-allele odds ratios (ORs) and 95% confidence intervals (CIs) using ordinal logistic regression models with TDLU measures as the outcome and SNPs as the explanatory variables. Associations with TDLU density were based on up to 680 women with genotype data, while associations with diameter and acini measures were based on up to 469 women with observed TDLUs. Results: The rs3803662 (TOX3/TNRC9) SNP risk allele showed an association with increased TDLU density, larger TDLUs, and more acini in TDLUs (TDLU density per-allele OR=1.29 95%CI=1.04-1.60; TDLU diameter OR=1.32 95%CI=1.00-1.74; and TDLU acini OR=1.34 95%CI=1.02-1.77), consistent with previous observations of significant associations seen for this SNP with mammographic density (a well-established risk factor for breast cancer), breast cancer risk, and survival of breast cancer. In addition, we observed associations for four other SNPs with TDLU density (rs311499, rs10483813, rs2981582, rs3817198), for one other SNP with mean TDLU diameter (rs11249433), and for three other SNPs with mean TDLU acini number (rs704010, rs10941679, rs11249433). Conclusion: These data suggest that breast cancer susceptibility SNPs may be associated with TDLU involution levels, and could represent a mechanism by which they influence breast cancer risk. These findings warrant replication in other studies and provide support for the concept that levels of TDLU involution represent an intermediate marker of breast cancer risk. Citation Format: Jonine D. Figueroa, Gretchen L. Gierach, Ruth Pfeiffer, Stephen Chanock, Louise Brinton, Deesha A. Patel, Daniel Visscher, Carolyn Mies, Stephen Hewitt, Susan Clare, Anna Maria Storniolo, Mark Sherman. Associations between breast cancer susceptibility markers and terminal duct lobular unit involution in normal breast tissues among women from the Susan G. Komen for the Cure® Tissue Bank. [abstract]. In: Proceedings of the AACR Special Conference on Post-GWAS Horizons in Molecular Epidemiology: Digging Deeper into the Environment; 2012 Nov 11-14; Hollywood, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2012;21(11 Suppl):Abstract nr 58.

AbstractBackgroundType 2 diabetes may increase the risk of amnestic mild cognitive impairment (aMCI) through Alzheimer's disease (AD)‐related and vascular pathology and may also increase the risk of nonamnestic MCI (naMCI) through vascular disease mechanisms. We examined the association of type 2 diabetes with mild cognitive impairment (MCI) and MCI subtype (aMCI and naMCI) overall and by sex.MethodsParticipants were Olmsted County, Minnesota residents (70 years and older) enrolled in a prospective, population‐based study. At baseline and every 15 months thereafter, participants were evaluated using the Clinical Dementia Rating scale, a neurological evaluation, and neuropsychological testing for a diagnosis of normal cognition, MCI, and dementia by a consensus panel. Type 2 diabetes was ascertained from the medical records of participants at baseline.ResultsOver a median 4.0 years of follow‐up, 348 of 1450 subjects developed MCI. Type 2 diabetes was associated (hazard ratio [95% confidence interval]) with MCI (1.39 [1.08–1.79]), aMCI (1.58 [1.17–2.15]; multiple domain: 1.58 [1.01–2.47]; single domain: 1.49 [1.09–2.05]), and the hazard ratio for naMCI was elevated (1.37 [0.84–2.24]). Diabetes was strongly associated with multiple‐domain aMCI in men (2.42 [1.31–4.48]) and an elevated risk of multiple domain naMCI in men (2.11 [0.70–6.33]), and with single domain naMCI in women (2.32 [1.04–5.20]).ConclusionsDiabetes was associated with an increased risk of MCI in elderly persons. The association of diabetes with MCI may vary with subtype, number of domains, and sex. Prevention and control of diabetes may reduce the risk of MCI and Alzheimer's disease.

Aberrant connectivity is implicated in many neurological and psychiatric disorders, including Alzheimer’s disease and schizophrenia. However, other than a few disease-associated candidate genes, we know little about the degree to which genetics play a role in the brain networks; we know even less about specific genes that influence brain connections. Twin and family-based studies can generate estimates of overall genetic influences on a trait, but genome-wide association scans (GWASs) can screen the genome for specific variants influencing the brain or risk for disease. To identify the heritability of various brain connections, we scanned healthy young adult twins with high-field, high-angular resolution diffusion MRI. We adapted GWASs to screen the brain’s connectivity pattern, allowing us to discover genetic variants that affect the human brain’s wiring. The association of connectivity with the SPON1 variant at rs2618516 on chromosome 11 (11p15.2) reached connectome-wide, genome-wide significance after stringent statistical corrections were enforced, and it was replicated in an independent subsample. rs2618516 was shown to affect brain structure in an elderly population with varying degrees of dementia. Older people who carried the connectivity variant had significantly milder clinical dementia scores and lower risk of Alzheimer’s disease. As a posthoc analysis, we conducted GWASs on several organizational and topological network measures derived from the matrices to discover variants in and around genes associated with autism ( MACROD2 ), development ( NEDD4 ), and mental retardation ( UBE2A ) significantly associated with connectivity. Connectome-wide, genome-wide screening offers substantial promise to discover genes affecting brain connectivity and risk for brain diseases.