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Duncan C Thomas

Publications and source records attributed to Duncan C Thomas.

At least 19 recordsLinked to original sources
PubMed2006

BRCA1 and BRCA2 mutation carriers, oral contraceptive use, and breast cancer before age 50.

BACKGROUND: Understanding the effect of oral contraceptives on risk of breast cancer in BRCA1 or BRCA2 mutation carriers is important because oral contraceptive use is a common, modifiable practice. METHODS: We studied 497 BRCA1 and 307 BRCA2 mutation carriers, of whom 195 and 128, respectively, had been diagnosed with breast cancer. Case-control analyses were conducted using unconditional logistic regression with adjustments for family history and familial relationships and were restricted to subjects with a reference age under 50 years. RESULTS: For BRCA1 mutation carriers, there was no significant association between risk of breast cancer and use of oral contraceptives for at least 1 year [odds ratio (OR), 0.77; 95% confidence interval (95% CI), 0.53-1.12] or duration of oral contraceptive use (P(trend) = 0.62). For BRCA2 mutation carriers, there was no association with use of oral contraceptives for at least 1 year (OR, 1.62; 95% CI, 0.90-2.92); however, there was an association of elevated risk with oral contraceptive use for at least 5 years (OR, 2.06; 95% CI, 1.08-3.94) and with duration of use (OR(trend) per year of use, 1.08; P = 0.008). Similar results were obtained when we considered only use of oral contraceptives that first started in 1975 or later. CONCLUSIONS: We found no evidence overall that use of oral contraceptives for at least 1 year is associated with breast cancer risk for BRCA1 and BRCA2 mutation carriers before age 50. For BRCA2 mutation carriers, use of oral contraceptives may be associated with an increased risk of breast cancer among women who use them for at least 5 years. Further studies reporting results separately for BRCA1 and BRCA2 mutation carriers are needed to resolve this important issue.

Adult↗
PubMed2006

Optimal two-stage genotyping designs for genome-wide association scans.

The much-anticipated fixed-array, genome-wide SNP genotyping technologies make large-scale genome-wide association scans now possible for large numbers of subjects. In this paper we reconsider the problem (Satagopan and Elston [2003] Genet Epidemiol 25:149-157) of optimizing a two-stage genotyping design to deal with important new issues that are relevant when studies are expanded from candidate gene size to a genome-wide scale. We investigate how the basic two-stage genotyping approach, in which all markers are genotyped in an initial group of subjects (stage I) and only the promising markers are genotyped in additional subjects (stage II), can be used to reduce genotyping cost in a genome-wide case-control association study even after allowing for much higher per genotype costs using specially designed assays in stage II, compared to the fixed array of SNPs used in stage I. In addition, we consider the problem of using measured SNPs to make (imperfect) prediction of unmeasured SNPs for association tests of all SNPs (measured or unmeasured) genome wide and the utility of expanding genotyping densities in stage II in the regions where significant associations were detected in stage I. Under a set of reasonable but conservative assumptions, we derive optimal two-stage design configurations (sample sizes and the thresholds of significance in both stages) with these optimal designs depending both on the total number of markers tested and upon the ratios of cost in stage II versus stage I. In addition we show how existing software for power and sample size calculations can be used for the purpose of designing two-stage studies, for a wide range of assumptions about the number of markers genotyped and the costs of genotyping in each stage of the study.

Case-Control Studies↗
PubMed2005

Recent developments in genomewide association scans: a workshop summary and review.

With the imminent availability of ultra-high-volume genotyping platforms (on the order of 100,000-1,000,000 genotypes per sample) at a manageable cost, there is growing interest in the possibility of conducting genomewide association studies for a variety of diseases but, so far, little consensus on methods to design and analyze them. In April 2005, an international group of >100 investigators convened at the University of Southern California over the course of 2 days to compare notes on planned or ongoing studies and to debate alternative technologies, study designs, and statistical methods. This report summarizes these discussions in the context of the relevant literature. A broad consensus emerged that the time was now ripe for launching such studies, and several common themes were identified--most notably the considerable efficiency gains of multistage sampling design, specifically those made by testing only a portion of the subjects with a high-density genomewide technology, followed by testing additional subjects and/or additional SNPs at regions identified by this initial scan.

Data Interpretation, Statistical↗
PubMed2005

A three-level model for binary time-series data: the effects of air pollution on school absences in the Southern California Children's Health Study.

A three-level model is proposed to simultaneously examine the effects of daily exposure to air pollution and individual risk factors on health outcomes without aggregating over subjects or time. We used a logistic transition model with random effects to take into account heterogeneity and overdispersion of the observations. A distributed lag structure for pollution has been included, assuming that the event on day t for a subject depends on the levels of air pollution for several preceding days. We illustrate this proposed model via detailed analysis of the effect of air pollution on school absenteeism based on data from the Southern California Children's Health Study.

Absenteeism↗
PubMed2005

BRCA1 variants in a family study of African-American and Latina women.

We sequenced the entire coding region of BRCA1 to improve our understanding of the frequency and nature of BRCA1 variants in African-American and Latina women identified from a multiethnic cohort in Los Angeles, California. The study included 109 African-American and 140 Latina sibships from families with two or more cases of breast or ovarian cancer among first-degree relatives. BRCA1 was sequenced in 278 breast or ovarian cancer cases and 229 unaffected sisters. The proportion of cases with known disease-causing mutations was low (0.72, 95% confidence interval: 0-1.7%). In total, 33 sequence variants were identified, including two protein truncation mutations, one deletion, and six silent and 24 missense variants. Two novel rare variants were identified that appeared to act as benign polymorphisms. Four rare variants may be unique to women of African descent based on existing literature, and three have been described exclusively in Latina women. The frequency of common variants was similar for cases and controls, but the frequency of common variants for African-American women significantly differed from those previously described for Caucasian women. We believe this to be the largest study of high-risk African-American and Latina women sequenced for variants in the BRCA1 gene to date.

Adult↗
PubMed2004

Case-sibling gene-association studies for diseases with variable age at onset.

Studies which compare cases to disease-free siblings are useful for assessing association between a genetic locus and a phenotypic trait, as they eliminate the possibility of confounding by population stratification. Many analytic methods for such family-based studies are based on a binary disease model. However, complex diseases have variable age at onset. Consequently, binary-outcome methods can be inefficient or biased. We review methods for analysing censored age-at-onset data from family studies, including stratified Cox regression and genotype-decomposition regression, an unstratified procedure which regresses age-at-onset on between- and within-family genotype components. We also introduce a retrospective likelihood for censored age-at-onset data, which requires an external estimate of the baseline hazard. Stratified Cox regression does not use controls who have not attained the age of their case sibling(s), potentially leading to a loss of efficiency. Both genotype-decomposition regression and the retrospective likelihood use these younger controls. We assess the performance of these methods via simulation studies. Stratified Cox regression and the retrospective likelihood have appropriate type I error rates in almost all situations studied; genotype-decomposition regression is often anti-conservative. Away from the null, confidence intervals for the relative risk derived from stratified Cox regression are anti-conservative when the disease is rare and case-rich families are sampled. The retrospective likelihood is more efficient than stratified Cox regression and its confidence intervals have correct coverage when the disease is rare or the estimate of the baseline hazard is reasonably accurate. These results suggest that when estimating genotype relative risks is the principal analytic goal, stratified Cox regression is appropriate as long as the disease is common; when the disease is rare, the retrospective likelihood may be more appropriate.

Age of Onset↗
PubMed2004

Study design: evaluating gene-environment interactions in the etiology of breast cancer - the WECARE study.

INTRODUCTION: Deficiencies in cellular responses to DNA damage can predispose to cancer. Ionizing radiation can cause cluster damage and double-strand breaks (DSBs) that pose problems for cellular repair processes. Three genes (ATM, BRCA1, and BRCA2) encode products that are essential for the normal cellular response to DSBs, but predispose to breast cancer when mutated. DESIGN: To examine the joint roles of radiation exposure and genetic susceptibility in the etiology of breast cancer, we designed a case-control study nested within five population-based cancer registries. We hypothesized that a woman carrying a mutant allele in one of these genes is more susceptible to radiation-induced breast cancer than is a non-carrier. In our study, 700 women with asynchronous bilateral breast cancer were individually matched to 1400 controls with unilateral breast cancer on date and age at diagnosis of the first breast cancer, race, and registry region, and counter-matched on radiation therapy. Each triplet comprised two women who received radiation therapy and one woman who did not. Radiation absorbed dose to the contralateral breast after initial treatment was estimated with a comprehensive dose reconstruction approach that included experimental measurements in anthropomorphic and water phantoms applying patient treatment parameters. Blood samples were collected from all participants for genetic analyses. CONCLUSIONS: Our study design improves the potential for detecting gene-environment interactions for diseases when both gene mutations and the environmental exposures of interest are rare in the general population. This is particularly applicable to the study of bilateral breast cancer because both radiation dose and genetic susceptibility have important etiologic roles, possibly by interactive mechanisms. By using counter-matching, we optimized the informativeness of the collected dosimetry data by increasing the variability of radiation dose within the case-control sets and enhanced our ability to detect radiation-genotype interactions.

Adult↗
PubMed2004

Toxicokinetic genetics: an approach to gene-environment and gene-gene interactions in complex metabolic pathways.

We propose an approach to modelling the joint effects of multiple genes involved in metabolic activation and detoxification of environmental exposures. A physiologically based pharmacokinetic (PBPK) model is used, in which the various person-specific metabolic rates are related to measurements of the genotypes and/or phenotypes at the various stages of the relevant pathways. Markov chain Monte Carlo (MCMC) methods are used to fit the model. We illustrate the approach by application to case-control data on colorectal polyps in relation to consumption of well-done red meat and tobacco smoking via pathways involving heterocyclic amines (regulated by the genes CYP1A2, NAT1 and NAT2) and polycyclic aromatic hydrocarbons (regulated by the genes CYP1A1, EPHX1 (also called mEH) and GSTM3). In this chapter, we focus on the biochemical basis for our conceptual models, deferring detailed mathematical description of the models and simulation results to a separate paper.

Arylamine N-Acetyltransferase↗