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Search Results: 1 - 10 of 170556 matches for " Lara E. Sucheston "
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Common Genetic Variants Are Associated with Accelerated Bone Mineral Density Loss after Hematopoietic Cell Transplantation
Song Yao, Lara E. Sucheston, Shannon L. Smiley, Warren Davis, Jeffrey M. Conroy, Norma J. Nowak, Christine B. Ambrosone, Philip L. McCarthy, Theresa Hahn
PLOS ONE , 2011, DOI: 10.1371/journal.pone.0025940
Abstract: Background Bone mineral density (BMD) loss commonly occurs after hematopoietic cell transplantation (HCT). Hypothesizing that genetic variants may influence post-HCT BMD loss, we conducted a prospective study to examine the associations of single nucleotide polymorphisms (SNP) in bone metabolism pathways and acute BMD loss after HCT. Methods and Findings We genotyped 122 SNPs in 45 genes in bone metabolism pathways among 121 autologous and allogeneic HCT patients. BMD changes from pre-HCT to day +100 post-HCT were analyzed in relation to these SNPs in linear regression models. After controlling for clinical risk factors, we identified 16 SNPs associated with spinal or femoral BMD loss following HCT, three of which have been previously implicated in genome-wide association studies of bone phenotypes, including rs2075555 in COL1A1, rs9594738 in RANKL, and rs4870044 in ESR1. When multiple SNPs were considered simultaneously, they explained 5–35% of the variance in post-HCT BMD loss. There was a significant trend between the number of risk alleles and the magnitude of BMD loss, with patients carrying the most risk alleles having the greatest loss. Conclusion Our data provide the first evidence that common genetic variants play an important role in BMD loss among HCT patients similar to age-related BMD loss in the general population. This infers that the mechanism for post-HCT bone loss is a normal aging process that is accelerated during HCT. A limitation of our study comes from its small patient population; hence future larger studies are warranted to validate our findings.
Pretreatment Serum Concentrations of 25-Hydroxyvitamin D and Breast Cancer Prognostic Characteristics: A Case-Control and a Case-Series Study
Song Yao,Lara E. Sucheston,Amy E. Millen,Candace S. Johnson,Donald L. Trump,Mary K. Nesline,Warren Davis,Chi-Chen Hong,Susan E. McCann,Helena Hwang,Swati Kulkarni,Stephen B. Edge,Tracey L. O'Connor,Christine B. Ambrosone
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0017251
Abstract: Results from epidemiologic studies on the relationship between vitamin D and breast cancer risk are inconclusive. It is possible that vitamin D may be effective in reducing risk only of specific subtypes due to disease heterogeneity.
Genetic Ancestry, Self-Reported Race and Ethnicity in African Americans and European Americans in the PCaP Cohort
Lara E. Sucheston, Jeannette T. Bensen, Zongli Xu, Prashant K. Singh, Leah Preus, James L. Mohler, L. Joseph Su, Elizabeth T. H. Fontham, Bernardo Ruiz, Gary J. Smith, Jack A. Taylor
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0030950
Abstract: Background Family history and African-American race are important risk factors for both prostate cancer (CaP) incidence and aggressiveness. When studying complex diseases such as CaP that have a heritable component, chances of finding true disease susceptibility alleles can be increased by accounting for genetic ancestry within the population investigated. Race, ethnicity and ancestry were studied in a geographically diverse cohort of men with newly diagnosed CaP. Methods Individual ancestry (IA) was estimated in the population-based North Carolina and Louisiana Prostate Cancer Project (PCaP), a cohort of 2,106 incident CaP cases (2063 with complete ethnicity information) comprising roughly equal numbers of research subjects reporting as Black/African American (AA) or European American/Caucasian/Caucasian American/White (EA) from North Carolina or Louisiana. Mean genome wide individual ancestry estimates of percent African, European and Asian were obtained and tested for differences by state and ethnicity (Cajun and/or Creole and Hispanic/Latino) using multivariate analysis of variance models. Principal components (PC) were compared to assess differences in genetic composition by self-reported race and ethnicity between and within states. Results Mean individual ancestries differed by state for self-reporting AA (p = 0.03) and EA (p = 0.001). This geographic difference attenuated for AAs who answered “no” to all ethnicity membership questions (non-ethnic research subjects; p = 0.78) but not EA research subjects, p = 0.002. Mean ancestry estimates of self-identified AA Louisiana research subjects for each ethnic group; Cajun only, Creole only and both Cajun and Creole differed significantly from self-identified non-ethnic AA Louisiana research subjects. These ethnicity differences were not seen in those who self-identified as EA. Conclusions Mean IA differed by race between states, elucidating a potential contributing factor to these differences in AA research participants: self-reported ethnicity. Accurately accounting for genetic admixture in this cohort is essential for future analyses of the genetic and environmental contributions to CaP.
Association of Rad51 polymorphism with DNA repair in BRCA1 mutation carriers and sporadic breast cancer risk
Luisel J Ricks-Santi, Lara E Sucheston, Yang Yang, Jo L Freudenheim, Claudine J Isaacs, Marc D Schwartz, Ramona G Dumitrescu, Catalin Marian, Jing Nie, Dominica Vito, Stephen B Edge, Peter G Shields
BMC Cancer , 2011, DOI: 10.1186/1471-2407-11-278
Abstract: Peripheral blood lymphoblasts from women with known BRCA1 mutations underwent the MSA (n = 138 among 20 families). BRCA1 and Rad51 genotyping and sequencing were performed to identify SNPs and haplotypes associated with the MSA. Positive associations from the study in high-risk families were subsequently examined in a population-based case-control study of breast cancer (n = 1170 cases and 2115 controls).Breast cancer diagnosis was significantly associated with the MSA among women from BRCA1 families (OR = 3.2 95%CI: 1.5-6.7; p = 0.004). The Rad51 5'UTR 135 C>G genotype (OR = 3.64; 95% CI: 1.38, 9.54; p = 0.02), one BRCA1 haplotype (p = 0.03) and in a polygenic model, the E1038G and Q356R BRCA1 SNPs were significantly associated with MBPC (p = 0.009 and 0.002, respectively). The Rad51 5'UTR 135C genotype was not associated with breast cancer risk in the population-based study.Mutagen sensitivity might be a useful biomarker of penetrance among women with BRCA1 mutations because the MSA phenotype is partially explained by genetic variants in BRCA1 and Rad51.The genetic determinants of breast cancer are under intensive study. Some women with a strong family history of breast cancer inherit BRCA1 or BRCA2 mutations, which have a variable penetrance for breast cancer, between 40 to 66% [1], suggesting that additional factors contribute to cancer risk among BRCA1 and BRCA2 carriers. For sporadic cancers, however, many low-penetrant single-nucleotide polymorphisms (SNPs) have been investigated in pathways ranging from growth factor signaling to DNA repair. Yet, it has been difficult to find consistency across study results [2-4], due to differences in study populations, sample sizes and study designs [5]. However, studies of high risk populations generally help uncover the molecular mechanisms of a disease and provide guidance and direction for studies of sporadic disease. While BRCA1 and BRCA2 mutations are highly penetrant [1], resulting in higher risk for breast cancer,
Information-theoretic gene-gene and gene-environment interaction analysis of quantitative traits
Pritam Chanda, Lara Sucheston, Song Liu, Aidong Zhang, Murali Ramanathan
BMC Genomics , 2009, DOI: 10.1186/1471-2164-10-509
Abstract: The KWII and the PAI were critically evaluated and incorporated within an algorithm called CHORUS for analyzing QT. The combinations with the highest values of KWII and PAI identified each known GEI associated with the QT in the simulated data sets. The CHORUS algorithm was tested using the simulated GAW15 data set and two real GGI data sets from QTL mapping studies of high-density lipoprotein levels/atherosclerotic lesion size and ultra-violet light-induced immunosuppression. The KWII and PAI were found to have excellent sensitivity for identifying the key GEI simulated to affect the two quantitative trait variables in the GAW15 data set. In addition, both metrics showed strong concordance with the results of the two different QTL mapping data sets.The KWII and PAI are promising metrics for analyzing the GEI of QT.The clinical presentation of many common complex diseases causing morbidity and mortality are associated with deviations from the population distributions of important quantitative traits (QT). For example, in hypertension and non-insulin dependent diabetes, the disease processes increase the QT, blood pressure and blood glucose, respectively. For many diseases, threshold values of QT are the basis for the diagnostic criteria for the diseases. However, obtaining an in-depth understanding of genetic and environmental determinants of QT such as weight, height and lifespan in healthy populations can also be important scientific questions. The regulation of many QT is typically complex and involves interactions among many genes as well as endogenous and exogenous factors [1,2]. For example, genes in pathways regulating appetite, metabolism, hormones and adipokines may interact with environmental factors such as diet and exercise to determine body weight. Nonetheless, the successful identification of the critical gene-environment interactions (GEI) involved in QT such as body weight can provide the scientific basis for preventative public health measures to re
Comparison of information-theoretic to statistical methods for gene-gene interactions in the presence of genetic heterogeneity
Lara Sucheston, Pritam Chanda, Aidong Zhang, David Tritchler, Murali Ramanathan
BMC Genomics , 2010, DOI: 10.1186/1471-2164-11-487
Abstract: The k-way interaction information (KWII) metric for identifying variable combinations involved in gene-gene interactions (GGI) was assessed using several simulated data sets under models of genetic heterogeneity driven by susceptibility increasing loci with varying allele frequency, penetrance values and heritability. The power and proportion of false positives of the KWII was compared to multifactor dimensionality reduction (MDR), restricted partitioning method (RPM) and logistic regression.The power of the KWII was considerably greater than MDR on all six simulation models examined. For a given disease prevalence at high values of heritability, the power of both RPM and KWII was greater than 95%. For models with low heritability and/or genetic heterogeneity, the power of the KWII was consistently greater than RPM; the improvements in power for the KWII over RPM ranged from 4.7% to 14.2% at for α = 0.001 in the three models at the lowest heritability values examined. KWII performed similar to logistic regression.Information theoretic models are flexible and have excellent power to detect GGI under a variety of conditions that characterize complex diseases.Numerous complex diseases such as cancer, cardiovascular disease, mental illnesses, and autoimmune disorders are the result of interactions among many exogenous and endogenous factors operating on one or more biological pathways. However, reliably identifying the key underlying gene-gene (GGI) and gene-environment interactions (GEI) has proven difficult because the number of interactions increases combinatorially with the number of variables considered and resultant high dimensionality presents significant statistical challenges in interaction analyses.Broadly, existing methods for analyzing GGI (and GEI) can be either parametric or non-parametric and can leverage dimensionality reduction or regression-based methodologies. Parametric approaches model explicitly the nature of the interaction, whereas the nonparamet
Variants in the vitamin D pathway, serum levels of vitamin D, and estrogen receptor negative breast cancer among African-American women: a case-control study
Song Yao, Gary Zirpoli, Dana H Bovbjerg, Lina Jandorf, Chi Chen Hong, Hua Zhao, Lara E Sucheston, Li Tang, Michelle Roberts, Gregory Ciupak, Warren Davis, Helena Hwang, Candace S Johnson, Donald L Trump, Susan E McCann, Foluso Ademuyiwa, Karen S Pawlish, Elisa V Bandera, Christine B Ambrosone
Breast Cancer Research , 2012, DOI: 10.1186/bcr3162
Abstract: In a case (n = 928)-control (n = 843) study of breast cancer in AA and EA women, we measured serum 25OHD levels in controls and tested associations between risk and tag single nucleotide polymorphisms (SNPs) in VDR, CYP24A1 and CYP27B1, particularly by ER status.More AAs had severe vitamin D deficiency (< 10 ng/ml) than EAs (34.3% vs 5.9%), with lowest levels among those with the highest African ancestry. Associations for SNPs differed by race. Among AAs, VDR SNP rs2239186, associated with higher serum levels of 25OHD, decreased risk after correction for multiple testing (OR = 0.53, 95% CI = 0.31-0.79, p by permutation = 0.03), but had no effect in EAs. The majority of associations were for ER-negative breast cancer, with seven differential associations between AA and EA women for CYP24A1 (p for interaction < 0.10). SNP rs27622941 was associated with a > twofold increased risk of ER-negative breast cancer among AAs (OR = 2.62, 95% CI = 1.38-4.98), but had no effect in EAs. rs2209314 decreased risk among EAs (OR = 0.38, 95% CI = 0.20-0.73), with no associations in AAs. The increased risk of ER-negative breast cancer in AAs compared to EAs was reduced and became non-significant (OR = 1.20, 95% CI = 0.80-1.79) after adjusting for these two CYP24A1 SNPs.These data suggest that genetic variants in the vitamin D pathway may be related to the higher prevalence of ER-negative breast cancer in AA women.American women of African ancestry (AA) are more likely to develop breast cancer at a younger age than those with European ancestry (EA) and are more likely to have tumors with aggressive characteristics, including high histological grade, negative estrogen receptor (ER) status, and basal-like - ER- and/or progesterone receptor (PR)-, HER2-, and cytokeratin 5/6+ and/or HER1+ -features [1,2]. The reasons for these racial disparities are unknown.It is clear that, among geographically diverse populations, certain genotypic and phenotypic characteristics may be selected for in res
Comparative survival analysis of breast cancer microarray studies identifies important prognostic genetic pathways
Jeffrey C Miecznikowski, Dan Wang, Song Liu, Lara Sucheston, David Gold
BMC Cancer , 2010, DOI: 10.1186/1471-2407-10-573
Abstract: Five microarray datasets related to breast cancer were examined using gene set analysis and the cancers were categorized into different subtypes using a scoring system based on genetic pathway activity.We have observed that significant genes in the individual studies show little reproducibility across the datasets. From our comparative analysis, using gene pathways with clinical variables is more reliable across studies and shows promise in assessing a patient's prognosis.This study concludes that, in light of clinical variables, there are significant gene pathways in common across the datasets. Specifically, several pathways can further significantly stratify patients for survival. These candidate pathways should help to develop a panel of significant biomarkers for the prognosis of breast cancer patients in a clinical setting.Developing genomic based biomarkers for breast cancer prognosis is an active research area with clinicians and researchers considering genomic expression data as a potential valuable source of information to be mined for such markers. In addition to considering the BRCA mutation status of a patient, three genetic markers, estrogen receptors (ER) [1], progesterone receptors (PR) [2], and the HER2/neu receptor (HER2) [3] are commonly used for assessing prognosis and/or assigning treatment. More recently TGF- has also been considered as a potential prognosis biomarker [4].One of the biggest challenges in developing valid prognostic genomic based biomarkers for breast cancer is obtaining large enough datasets with sufficient patient follow-up time [5,6]. To address this, we employ a comparative analysis approach. In a comparative analysis, several datasets gathered to test related hypotheses are combined to obtain more powerful estimates for a common hypothesis. We combine five genomic studies examining prognosis in breast cancer patients to assess the ability of the genetic biomarkers to stratify or distinguish patient survival. Datasets under c
Inherited Variants in Regulatory T Cell Genes and Outcome of Ovarian Cancer
Ellen L. Goode, Melissa DeRycke, Kimberly R. Kalli, Ann L. Oberg, Julie M. Cunningham, Matthew J. Maurer, Brooke L. Fridley, Sebastian M. Armasu, Daniel J. Serie, Priya Ramar, Krista Goergen, Robert A. Vierkant, David N. Rider, Hugues Sicotte, Chen Wang, Boris Winterhoff, Catherine M. Phelan, Joellen M. Schildkraut, Rachel P. Weber, Ed Iversen, Andrew Berchuck, Rebecca Sutphen, Michael J. Birrer, Shalaka Hampras, Leah Preus, Simon A. Gayther, Susan J. Ramus, Nicolas Wentzensen, Hannah P. Yang, Montserrat Garcia-Closas, Honglin Song, Jonathan Tyrer, Paul P. D. Pharoah, Gottfried Konecny, Thomas A. Sellers, Roberta B. Ness, Lara E. Sucheston, Kunle Odunsi, Lynn C. Hartmann, Kirsten B. Moysich, Keith L. Knutson
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0053903
Abstract: Although ovarian cancer is the most lethal of gynecologic malignancies, wide variation in outcome following conventional therapy continues to exist. The presence of tumor-infiltrating regulatory T cells (Tregs) has a role in outcome of this disease, and a growing body of data supports the existence of inherited prognostic factors. However, the role of inherited variants in genes encoding Treg-related immune molecules has not been fully explored. We analyzed expression quantitative trait loci (eQTL) and sequence-based tagging single nucleotide polymorphisms (tagSNPs) for 54 genes associated with Tregs in 3,662 invasive ovarian cancer cases. With adjustment for known prognostic factors, suggestive results were observed among rarer histological subtypes; poorer survival was associated with minor alleles at SNPs in RGS1 (clear cell, rs10921202, p = 2.7×10?5), LRRC32 and TNFRSF18/TNFRSF4 (mucinous, rs3781699, p = 4.5×10?4, and rs3753348, p = 9.0×10?4, respectively), and CD80 (endometrioid, rs13071247, p = 8.0×10?4). Fo0r the latter, correlative data support a CD80 rs13071247 genotype association with CD80 tumor RNA expression (p = 0.006). An additional eQTL SNP in CD80 was associated with shorter survival (rs7804190, p = 8.1×10?4) among all cases combined. As the products of these genes are known to affect induction, trafficking, or immunosuppressive function of Tregs, these results suggest the need for follow-up phenotypic studies.
Complex Segregation Analysis of Pedigrees from the Gilda Radner Familial Ovarian Cancer Registry Reveals Evidence for Mendelian Dominant Inheritance
Bamidele O. Tayo,Richard A. DiCioccio,Yulan Liang,Maurizio Trevisan,Richard S. Cooper,Shashikant Lele,Lara Sucheston,Steven M. Piver,Kunle Odunsi
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0005939
Abstract: Familial component is estimated to account for about 10% of ovarian cancer. However, the mode of inheritance of ovarian cancer remains poorly understood. The goal of this study was to investigate the inheritance model that best fits the observed transmission pattern of ovarian cancer among 7669 members of 1919 pedigrees ascertained through probands from the Gilda Radner Familial Ovarian Cancer Registry at Roswell Park Cancer Institute, Buffalo, New York.
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