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In this study, we estimated the association between the inferred haplotypes in the inflammation, DNA repair, and folate pathways, and developed risk models for Hodgkin Lymphoma. The study population consisted of 200 Hodgkin Lymphoma cases and 220 controls. A susceptible association was observed on the XPC gene with Haplotype CT (rs2228001 and rs2228000), and a protective association was observed on the IL4R gene with Haplotype TCA (rs1805012, rs1805015, and rs1801275). These results can provide the necessary tools to identify high-risk individuals after validation in large data sets.

Purpose: The development of second primary tumors (SPT) or recurrence alters prognosis for curatively treated head and neck squamous cell carcinoma (HNSCC) patients. The 13-cis-Retinoic acid (13-cRA) has been tested as a chemoprevention agent in clinical trials with mixed results. Therefore, we investigated whether genetic variants in the PI3K/PTEN/AKT/mTOR pathway could serve as biomarkers to identify which patients are at high risk of an SPT/recurrence, while also predicting response to 13-cRA chemoprevention. Experimental Design: A total of 137 pathway single-nucleotide polymorphisms were genotyped in 440 patients from the Retinoid Head and Neck Second Primary Trial and assessed for SPT/recurrence risk and response to 13-cRA. Risk models were created based on epidemiology, clinical, and genetic data. Results: Twenty-two genetic loci were associated with increased SPT/recurrence risk, with six also being associated with a significant benefit following chemoprevention. Combined analysis of these high-risk/high-benefit loci identified a significant (P = 1.54 × 10−4) dose–response relationship for SPT/recurrence risk, with patients carrying four to five high-risk genotypes having a 3.76-fold [95% Confidence Interval (CI), 1.87–7.57] increase in risk in the placebo group (n = 215). Patients carrying four to five high-risk loci showed the most benefit from 13-cRA chemoprevention, with a 73% reduction in SPT/recurrence (95% CI, 0.13–0.58) compared with those with the same number of high-risk genotypes who were randomized to receive placebo. Incorporation of these loci into a risk model significantly improved the discriminatory ability over models with epidemiology, clinical, and previously identified genetic variables. Conclusions: These results show that loci within this important pathway could identify individuals with a high-risk/high-benefit profile and are a step toward personalized chemoprevention for HNSCC patients. Clin Cancer Res; 18(13); 3705–13. ©2012 AACR.

Background: Tobacco-induced lung cancer is characterized by a deregulated inflammatory microenvironment. Variants in multiple genes in inflammation pathways may contribute to risk of lung cancer. Methods: We therefore conducted a three-stage comprehensive pathway analysis (discovery, replication, and meta-analysis) of inflammation gene variants in ever-smoking lung cancer cases and controls. A discovery set (1,096 cases and 727 controls) and an independent and nonoverlapping internal replication set (1,154 cases and 1,137 controls) were derived from an ongoing case–control study. For discovery, we used an iSelect BeadChip to interrogate a comprehensive panel of 11,737 inflammation pathway single-nucleotide polymorphisms (SNP) and selected nominally significant (P < 0.05) SNPs for internal replication. Results: There were six SNPs that achieved statistical significance (P < 0.05) in the internal replication data set with concordant risk estimates for former smokers and five concordant and replicated SNPs in current smokers. Replicated hits were further tested in a subsequent meta-analysis using external data derived from two published genome-wide association studies (GWAS) and a case–control study. Two of these variants (a BCL2L14 SNP in former smokers and an SNP in IL2RB in current smokers) were further validated. In risk score analyses, there was a 26% increase in risk with each additional adverse allele when we combined the genotyped SNP and the most significant imputed SNP in IL2RB in current smokers and a 36% similar increase in risk for former smokers associated with genotyped and imputed BCL2L14 SNPs. Conclusions/Impact: Before they can be applied for risk prediction efforts, these SNPs should be subject to further external replication and more extensive fine mapping studies. Cancer Epidemiol Biomarkers Prev; 21(7); 1213–21. ©2012 AACR.

Intervention trials such as studies on smoking cessation may observe multiple, discrete outcomes over time. When the outcome is binary, participant observations may alternate between two states over the course of the study. The generalized estimating equation (GEE) approach is commonly used to analyze binary, longitudinal data in the context of independent variables. However, the sequence of observations may be assumed to follow a Markov chain with stationary transition probabilities when observations are made at fixed time points. Participants favoring the transition to one particular state over the other would be evidence of a trend in the observations. Using a log-transformed trend parameter, the determinants of a trend in a binary, longitudinal study may be evaluated by maximizing the likelihood function. A new methodology is presented here to test for the presence and determinants of a trend in binary, longitudinal observations. Empirical studies are evaluated and comparisons are made with the GEE ap...

Background: Established psychosocial risk factors increase the risk for experimentation among Mexican origin youth. Now, we comprehensively investigate the added contribution of select polymorphisms in candidate genetic pathways associated with sensation seeking, risk taking, and smoking phenotypes to predict experimentation. Methods: Participants (N = 1,118 Mexican origin youth) recruited from a large population-based cohort study in Houston, TX, provided prospective data on cigarette experimentation over 3 years. Psychosocial data were elicited twice—baseline and final follow-up. Participants were genotyped for 672 functional and tagging variants in the dopamine, serotonin, and opioid pathways. Results: After adjusting for gender and age, with a Bayesian False Discovery Probability set at 0.8 and prior probability of 0.05, six gene variants were significantly associated with risk of experimentation. After controlling for established risk factors, multivariable analyses revealed that participants with six or more risk alleles were 2.25 [95% confidence interval (CI), 1.62–3.13] times more likely to have experimented since baseline than participants with five or fewer. Among committed never-smokers (N = 872), three genes (OPRM1, SNAP25, HTR1B) were associated with experimentation as were all psychosocial factors. Among susceptible youth (N = 246), older age at baseline, living with a smoker, and three different genes (HTR2A, DRD2, SLC6A3) predicted experimentation. Conclusions: Our findings, which have implications for development of culturally specific interventions, need to be validated in other ethnic groups. Impact: These results suggest that variations in select genes interact with a cognitive predisposition toward smoking. In susceptible adolescents, the impact of the genetic variants appears to be larger than committed never-smokers. Cancer Epidemiol Biomarkers Prev; 21(1); 228–38. ©2011 AACR.

Background: Breast cancer is associated with treatment-related infertility and has been demonstrated to be a major concern for premenopausal survivors. Detection of a BRCA deleterious mutation may also affect attitudes regarding future childbearing. Preimplantation genetic diagnosis (PGD) allows women to use in vitro fertilization (IVF) to implant only those embryos without a BRCA mutation. The ability to test the fetus for BRCA mutations is also available through amniocentesis and chorionic villus sampling (CVS). The objective of this study was to evaluate attitudes about childbearing and fertility in women being evaluated for a BRCA mutation. Methods: Women with childbearing potential who were referred to the Clinical Cancer Genetics Clinic to be evaluated for a BRCA mutation were invited to participate in this survey. The questionnaire was administered prior to genetic counseling. A follow-up was administered after the BRCA results were disclosed. The survey queried participants regarding their attitudes on fertility, pregnancy as it may relate to cancer and the potential of a BRCA mutation. Other questions detailed attitudes regarding IVF, PGD, and CVS in these instances. Descriptive statistics were used. Results: One hundred and twenty-eight women completed pre-questionnaires and to date 76 have completed post results disclosure questionnaires. The mean age was 33 (range 21–44) with 69.5% with a diagnosis of breast cancer, 39.8% received chemotherapy and 60.9% already had at least 1 biological child. A future child was desired by 45.3% although 53.1% worried that their children would have an increased risk of cancer. Regarding PGD, although only 30.9% (38/123) said that they would use PGD, 80.2% felt that the testing should be available to families with inherited cancers. Regarding fetal testing via amniocentesis or CVS, 29.7% would have the fetus tested and 7% would consider termination if a genetic mutation was identified. Additionally, 69.5% felt it was important to receive fertility counseling and treatment at the same place where they receive their cancer care. To date 8 women have been diagnosed with a BRCA1 mutation and 4 with a BRCA2 mutation. When asked similar questions after their genetic results were disclosed, 2 women who had previously stated they would not use PGD changed their mind. Conclusions: Future pregnancies are important to many breast cancer survivors. BRCA mutation carriers have the option to have children without passing on their genetic risk for cancer. Although few would use these interventions, a large majority felt it was important to have information about these choices and to have options for fertility preservation options addressed at the center where cancer care is delivered. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P2-13-05.

Hereditary breast and ovarian cancer syndrome (HBOC) related to the breast cancer (BRCA) genes initially was identified in families with the use of genetic linkage analysis.1–3 Since then, over 5000 different mutations in these genes have been identified that are inherited in an autosomal-dominant fashion and are responsible for approximately 5% to 10% of breast cancer diagnoses.4 Carriers of this mutation have an elevated risk of developing both breast and/or ovarian cancer, and a meta-analysis estimate of the lifetime risk of breast cancer was 47% to 66% in BRCA1 carriers and 40% to 57% in the BRCA2 carriers, and the risk of developing ovarian cancer was 35% to 46% and 13% to 23%, respectively, in the same analysis.5 One of the major risk factors for HBOC is the development of breast cancer at a very young age, Thus, the National Comprehensive Cancer Network (NCCN) guidelines panel has recommend initiating screening at ages 20 to 25 years, or 5 to 10 years earlier than the youngest age at diagnosis in the family.6 Implementing screening techniques is meant to identify cancers at the earliest time possible; therefore, estimating the onset of disease is vital in timing the initiation of screening and interventions. Anticipation has been described as a phenomenon observed in inherited diseases such as Fragile X syndrome and Huntington disease, in which the disease occurs at younger ages or with increased severity of disease in subsequent generations.7,8 The cause of this anticipation has been identified as DNA instability, such as nucleotide repeats that change in length in subsequent generations, altering the phenotype of the disease. However, changes in disease phenotype in subsequent generations also have been identified in other disorders, such as in colon cancer, Alzheimer disease, and diabetes.9,10 With the increase in BRCA1 and BRCA2 testing, there also has been an increase in families being evaluated and screened for HBOC. There have been several reports of anticipation in breast cancer. To date, these reports have been based on very small cohorts; those studies indicated an earlier age at diagnosis and examined the absolute differences between matched pairs. Dagan and Gershoni-Baruch reported a statistically significant difference of approximately 4 years in BRCA2 mutation carriers and a statistically nonsignificant numerical difference in BRCA1 carriers.11 In addition, Peixoto et al and Paltiel et al also observed similar patterns of earlier age of diagnosis for subsequent generations in breast cancer registries.12,13 When discussing appropriate screening interventions for women with a known deleterious BRCA1 or BRCA2 mutation, potential interventions include clinical breast examination, magnetic resonance imaging, and mammography.14 Evaluating for patterns of inheritance like anticipation in families with known deleterious BRCA mutations may help promote understanding of these genes and provide further insight into the timing of screening initiation and starting other interventions. The objective of the current analysis was to evaluate any trends in age at diagnoses in families with known deleterious BRCA mutations at a single institution to add to the growing evidence of genetic anticipation in patients with HBOC. We evaluated families who were referred to the Clinical Cancer Genetic Program at our institution and analyzed age at diagnosis across 2 generations.

Background Neurocognitive impairment occurs in 20%-40% of childhood acute lymphoblastic leukemia (ALL) survivors, possibly mediated by folate depletion and homocysteine elevation following methotrexate treatment. We evaluated the relationship between folate pathway polymorphisms and neurocognitive impairment after childhood ALL chemotherapy.

DNA repair variants may play a potentially important role in an individual's susceptibility to developing cancer. Numerous studies have reported the association between genetic single nucleotide polymorphisms (SNPs) in DNA repair genes and different types of hematologic cancers. However, to date, the effects of such SNPs on modulating Hodgkin lymphoma (HL) risk have not yet been investigated. We hypothesized that gene-gene interaction between candidate genes in direct reversal, nucleotide excision repair (NER), base excision repair (BER) and double strand break (DSB) pathways may contribute to susceptibility to HL. To test this hypothesis, we conducted a study on 200 HL cases and 220 controls to assess associations between HL risk and 21 functional SNPs in DNA repair genes. We evaluated potential gene-gene interactions and the association of multiple polymorphisms in a chromosome region using a multi-analytic strategy combining logistic regression, multi-factor dimensionality reduction and classification and regression tree approaches. We observed that, in combination, allelic variants in the XPC Ala499Val, NBN Glu185Gln, XRCC3 Thr241Me, XRCC1 Arg194Trp, and XRCC1 399Gln polymorphisms modify the risk for developing HL. Moreover, the cumulative genetic risk score revealed a significant trend where the risk for developing HL increases as the number of adverse alleles in BER and DSB genes increase. These findings suggest that DNA repair variants in BER and DSB pathways may play an important role in the development of HL.

Lung cancer risk prediction models hold the promise of improving patient care and streamlining research. The ultimate goal of these models is to inform clinicians as to which interventions their individual patients should receive to reduce lung cancer-associated morbidity and mortality. In this paper, we discuss the history and current state of lung cancer prediction models, focusing on three models: the Bach model, the Spitz model, and the Liverpool Lung Project (LLP) model. We also discuss the prospects for further development of improved prediction models for lung cancer risk. Although current models can identify those smokers at highest risk for lung cancer, these models are presently of limited use in the clinical setting. Nevertheless, lung cancer risk prediction models can be used during study enrollment to select more appropriate study subjects, and may eventually be useful in identifying patients for lung cancer screening or to receive chemoprevention.

BackgroundCardiovascular (CV) risk stratification for patients with rheumatoid arthritis (RA) should facilitate evidence-based management. Prior work has derived an internally validated a CV risk score, the Expanded Cardiovascular Risk Prediction Score for Rheumatoid Arthritis (ERS-RA), using US data. The aim of this study was to perform an external validation among unselected patients with RA from Europe.MethodsThree large, partially overlapping, cohorts of patients with RA from the Swedish Rheumatology Quality register were identified for external validation, two with information on smoking and two with close to 10 years of median follow-up. The 10 -year rate of first CV events was assessed using the Kaplan-Meier method. The performance of ERS-RA was assessed using C-index and comparisons of observed versus predicted risks.ResultsThe C-index for ERS-RA varied across the three RA cohorts, from 0.75 to 0.78. Predicted risks corresponded well to observed risks among individuals with ≤10 % observed 10- year CV risk, but underestimated risk in individuals with a higher observed risk. In the absence of data on smoking, ERS-RA underestimated the CV risk by 3.3%, whereas in the cohorts including data on smoking, the calibration was within 1% (0.06% and 0.7%). In the clinically relevant risk intervals (ConclusionsIn an unselected Swedish population with RA, ERS-RA performed well, although the 10-year CV risk was underestimated in high-risk groups and in the absence of data on smoking. ERS-RA could be considered as a risk stratification tool for targeted preventive interventions in clinical rheumatology practice.

Cancer risk assessment is a multidisciplinary process that goes beyond the scope of classical epidemiology to include the biological evaluation of individual differences to carcinogenic exposures. The inclusion of genetic biomarkers such as mutagen sensitivity or cytokinesis-blocked micronucleus (CBMN) assay end points into risk assessment models allows for a more comprehensive determination of cancer risk that includes known demographic (age and gender), lifestyle exposures (smoking and alcohol) and occupational or environmental exposures. The CBMN assay generates multiple correlated end points that, after applying data reduction methods, could be combined into a summary measure that incorporates information from each individual variable into a single (or possible multiple, uncorrelated) measure of risk. In this article, we highlight the use of the CBMN assay in radiosensitivity assessment. In addition, we demonstrate the potential use of the combined summary measures in cancer risk assessment as a result of chronic exposure to tobacco carcinogens. The simplicity, rapidity and sensitivity of the CBMN assay not only make it a valuable tool for screening but also the multiple end points simultaneously generated lead to a better understanding of the underlying mechanisms involved in the carcinogenic process that could in turn substantially improve risk predictions.

Missing data often occur in cross-sectional surveys and longitudinal and experimental studies. The purpose of this study was to compare the prediction of self-rated health (SRH), a robust predictor of morbidity and mortality among diverse populations, before and after imputation of the missing variable "yearly household income." We reviewed data from 4,162 participants of Mexican origin recruited from July 1, 2002, through December 31, 2005, and who were enrolled in a population-based cohort study. Missing yearly income data were imputed using three different single imputation methods and one multiple imputation under a Bayesian approach. Of 4,162 participants, 3,121 were randomly assigned to a training set (to derive the yearly income imputation methods and develop the health-outcome prediction models) and 1,041 to a testing set (to compare the areas under the curve (AUC) of the receiver-operating characteristic of the resulting health-outcome prediction models). The discriminatory powers of the SRH prediction models were good (range, 69-72%) and compared to the prediction model obtained after no imputation of missing yearly income, all other imputation methods improved the prediction of SRH (P < 0.05 for all comparisons) with the AUC for the model after multiple imputation being the highest (AUC = 0.731). Furthermore, given that yearly income was imputed using multiple imputation, the odds of SRH as good or better increased by 11% for each $5,000 increment in yearly income. This study showed that although imputation of missing data for a key predictor variable can improve a risk health-outcome prediction model, further work is needed to illuminate the risk factors associated with SRH.

In genome-wide association studies, inherited risk of glioma has been demonstrated for rare familial syndromes and with common variants from 3–5 chromosomal regions. To assess the degree of familial aggregation of glioma, the authors performed a pooled analysis of data from 2 large glioma case-control studies in the United States (MD Anderson Cancer Center, Houston, Texas (1994–2006) and University of California, San Francisco (1991–2004)) and from the Swedish Cancer Registry (1958–2006) to measure excess cases of cancer among first-degree relatives of glioma probands. This analysis included 20,377 probands with glioma and 52,714 first-degree relatives. No overall increase was found in the expected number of cancers among family members; however, there were 77% more gliomas than expected. There were also significantly more sarcoma and melanoma cases than expected, which is supported by evidence in the literature, whereas there were significantly fewer-than-expected cases of leukemia, non-Hodgkin lymphoma, and bladder, lung, pancreatic, prostate, and uterine cancers. This large pooled analysis provided sufficient numbers of related family members to examine the genetic mechanisms involved in the aggregation of glioma with other cancers in these families. However, misclassification due to unvalidated cancers among family members could account for the differences seen by study site.

BACKGROUND: Overall, Latinas are more likely to be diagnosed with a more advanced stage of breast cancer and are 20% more likely to die of breast cancer than non-Hispanic white women. It is estimated that from 2003 to 2006, $82.0 billion in direct medical care expenditures, in addition to 100,000 lives annually, could be saved by eliminating health disparities experienced by Latinos and increasing the use of up to 5 preventive services in the United States. An additional 3700 lives could be saved if 90% of women aged ≥40 years were recently screened for breast cancer. METHODS: The authors examined the risk for breast cancer in a case-control, population-based sample of Mexican-origin women in Harris County, Texas (n = 714), where the rates of breast cancer mortality for Latina women have doubled since 1990. RESULTS: Half of breast cancer cases (n = 119) were diagnosed in women aged

Background: DNA strand breaks pose the greatest threat to genomic stability. Genetically determined mutagen sensitivity predisposes individuals to a variety of cancers, including glioma. However, polymorphisms in DNA strand break repair genes that may determine mutagen sensitivity are not well studied in cancer risk, especially in gliomas. Methods: We correlated genotype data for tag single-nucleotide polymorphisms (tSNPs) of DNA strand break repair genes with a gamma-radiation-induced mutagen sensitivity phenotype [expressed as mean breaks per cell (B/C)] in samples from 426 glioma patients. We also conducted analysis to assess joint and haplotype effects of single-nucleotide polymorphisms (SNPs) on mutagen sensitivity. We further validate our results in an independent external control group totaling 662 subjects. Results: Of the 392 tSNPs examined, we found that mutagen sensitivity was modified by one tSNP in the EME2 gene and six tSNPs in the RAD51L1 gene (P < 0.01). Among the six RAD51L1 SNPs tested in the validation set, one (RAD51L1 rs2180611) was significantly associated with mutagen sensitivity (P = 0.025). Moreover, we found a significant dose–response relationship between the mutagen sensitivity and the number of adverse tSNP genotypes. Furthermore, haplotype analysis revealed that RAD51L1 haplotypes F-A (zero adverse allele) and F-E (six adverse alleles) exhibited the lowest (0.42) and highest (0.93) mean B/C values, respectively. A similar dose–response relationship also existed between the mutagen sensitivity and the number of adverse haplotypes. Conclusion: These results suggest that polymorphisms in and haplotypes of the RAD51L1 gene, which is involved in the double-strand break repair pathway, modulate gamma-radiation-induced mutagen sensitivity.

Purpose Glioblastoma (GBM) is the most common and aggressive type of glioma and has the poorest survival. However, a small percentage of patients with GBM survive well beyond the established median. Therefore, identifying the genetic variants that influence this small number of unusually long-term survivors may provide important insight into tumor biology and treatment. Patients and Methods Among 590 patients with primary GBM, we evaluated associations of survival with the 100 top-ranking glioma susceptibility single nucleotide polymorphisms from our previous genome-wide association study using Cox regression models. We also compared differences in genetic variation between short-term survivors (STS; ≤ 12 months) and long-term survivors (LTS; ≥ 36 months), and explored classification and regression tree analysis for survival data. We tested results using two independent series totaling 543 GBMs. Results We identified LIG4 rs7325927 and BTBD2 rs11670188 as predictors of STS in GBM and CCDC26 rs10464870 and rs891835, HMGA2 rs1563834, and RTEL1 rs2297440 as predictors of LTS. Further survival tree analysis revealed that patients ≥ 50 years old with LIG4 rs7325927 (V) had the worst survival (median survival time, 1.2 years) and exhibited the highest risk of death (hazard ratio, 17.53; 95% CI, 4.27 to 71.97) compared with younger patients with combined RTEL1 rs2297440 (V) and HMGA2 rs1563834 (V) genotypes (median survival time, 7.8 years). Conclusion Polymorphisms in the LIG4, BTBD2, HMGA2, and RTEL1 genes, which are involved in the double-strand break repair pathway, are associated with GBM survival.

The impact of single-nucleotide polymorphisms (SNPs) of the DNA repair gene XPC on DNA repair capacity (DRC) and genotoxicity has not been comprehensively determined. We constructed a comprehensive haplotype map encompassing all common XPC SNPs and evaluated the effect of Bayesian-inferred haplotypes on DNA damage associated with tobacco smoking, using chromosome aberrations (CA) as a biomarker. We also used the mutagen-sensitivity assay, in which mutagen-induced CA in cultured lymphocytes are determined, to evaluate the haplotype effects on DRC. We hypothesized that if certain XPC haplotypes have functional effects, a correlation between these haplotypes and baseline and/or mutagen-induced CA would exist. Using HapMap and single nucleotide polymorphism (dbSNP) databases, we identified 92 SNPs, of which 35 had minor allele frequenciesor= 0.05. Bayesian inference and subsequent phylogenetic analysis identified 21 unique haplotypes, which segregated into six distinct phylogenetically grouped haplotypes (PGHs A-F). A SNP tagging approach used identified 11 tagSNPs representing these 35 SNPs (r(2) = 0.80). We utilized these tagSNPs to genotype a population of smokers matched to nonsmokers (n = 123). Haplotypes for each individual were reconstituted and PGH designations were assigned. Relationships between XPC haplotypes and baseline and/or mutagen-induced CA were then evaluated. We observed significant interaction among smoking and PGH-C (p = 0.046) for baseline CA where baseline CA was 3.5 times higher in smokers compared to nonsmokers. Significant interactions among smoking and PGH-D (p = 0.023) and PGH-F (p = 0.007) for mutagen-induced CA frequencies were also observed. These data indicate that certain XPC haplotypes significantly alter CA and DRC in smokers and, thus, can contribute to cancer risk.

Lynch syndrome is an autosomal dominant syndrome of familial malignancies resulting from germ line mutations in DNA mismatch repair (MMR) genes. Our goal was to take a pathway-based approach to investigate the influence of polymorphisms in cell cycle-related genes on age of onset for Lynch syndrome using a tree model.We evaluated polymorphisms in a panel of cell cycle-related genes (AURKA, CDKN2A, TP53, E2F2, CCND1, TP73, MDM2, IGF1, and CDKN2B) in 220 MMR gene mutation carriers from 129 families. We applied a novel statistical approach, tree modeling (Classification and Regression Tree), to the analysis of data on patients with Lynch syndrome to identify individuals with a higher probability of developing colorectal cancer at an early age and explore the gene-gene interactions between polymorphisms in cell cycle genes.We found that the subgroup with CDKN2A C580T wild-type genotype, IGF1 CA-repeatsor=19, E2F2 variant genotype, AURKA wild-type genotype, and CCND1 variant genotype had the youngest age of onset, with a 45-year median onset age, while the subgroup with CDKN2A C580T wild-type genotype, IGF1 CA-repeatsor=19, E2F2 wild-type genotype, and AURKA variant genotype had the latest median age of onset, which was 70 years. Furthermore, we found evidence of a possible gene-gene interaction between E2F2 and AURKA genes related to CRC age of onset.Polymorphisms in these cell cycle-related genes work together to modify the age at the onset of CRC in patients with Lynch syndrome. These studies provide an important part of the foundation for development of a model for stratifying age of onset risk among those with Lynch syndrome.

BACKGROUND. The p53 tumor suppressor protein homolog p73 can be inactivated by oncoprotein E6 of human papillomavirus (HPV). Variation in p73 may alter the interaction between the E6 protein and p73 and, thus, alter the risk for HPV-associated carcinogenesis. It is believed that the p73 G4C14-to-A4T14 polymorphism affects p73 function by altering gene expression; however, whether that polymorphism also alters the risk of HPV type 16 (HPV-16)-associated squamous cell carcinoma of the oropharynx (SCCOP) is unknown. METHODS. The current case-control study included a case group of 188 non-Hispanic white patients with newly diagnosed SCCOP and a control group of 349 healthy individuals. Logistic regression analyses were used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for cases and controls stratified by p73 genotype, age, sex, smoking status, alcohol use, and HPV-16 status. The effects of p73 genotypes on the risk of HPV-16-associated SCCOP were explored with further stratification by smoking and drinking status. RESULTS. HPV-16 seropositivity was associated with an increased risk of SCCOP (adjusted OR, 5.98; 95% CI, 3.89-9.20), especially among never smokers (adjusted OR, 13.8; 95% CI, 5.91-32.1), never drinkers (adjusted OR, 14.9; 95% CI, 5.24-42.4), and individuals with p73 variant genotypes (GC/AT and AT/AT; adjusted OR, 7.96; 95% CI, 3.83-16.5). Moreover, the risk of HPV-16-associated SCCOP for individuals who had p73 variant genotypes was particularly high in never smokers and never drinkers. CONCLUSIONS. The p73 G4C14-to-A4T14 polymorphism may modulate the risk of HPV-16-associated SCCOP, and the p73 variant genotypes may be markers of genetic susceptibility to HPV-16-associated SCCOP, particularly in never smokers and never drinkers. Cancer 2008. © 2008 American Cancer Society.

Because existing risk prediction models for lung cancer were developed in white populations, they may not be appropriate for predicting risk among African-Americans. Therefore, a need exists to construct and validate a risk prediction model for lung cancer that is specific to African-Americans. We analyzed data from 491 African-Americans with lung cancer and 497 matched African-American controls to identify specific risks and incorporate them into a multivariable risk model for lung cancer and estimate the 5-year absolute risk of lung cancer. We performed internal and external validations of the risk model using data on additional cases and controls from the same ongoing multiracial/ethnic lung cancer case-control study from which the model-building data were obtained as well as data from two different lung cancer studies in metropolitan Detroit, respectively. We also compared our African-American model with our previously developed risk prediction model for whites. The final risk model included smoking-related variables [smoking status, pack-years smoked, age at smoking cessation (former smokers), and number of years since smoking cessation (former smokers)], self-reported physician diagnoses of chronic obstructive pulmonary disease or hay fever, and exposures to asbestos or wood dusts. Our risk prediction model for African-Americans exhibited good discrimination [75% (95% confidence interval, 0.67–0.82)] for our internal data and moderate discrimination [63% (95% confidence interval, 0.57–0.69)] for the external data group, which is an improvement over the Spitz model for white subjects. Existing lung cancer prediction models may not be appropriate for predicting risk for African-Americans because (a) they were developed using white populations, (b) level of risk is different for risk factors that African-American share with whites, and (c) unique group-specific risk factors exist for African-Americans. This study developed and validated a risk prediction model for lung cancer that is specific to African-Americans and thus more precise in predicting their risks. These findings highlight the importance of conducting further ethnic-specific analyses of disease risk.

The multi-endpoint cytokinesis-blocked micronucleus assay is used for assessing chromosome aberrations. We have recently reported that this assay is extremely sensitive to genetic damage caused by the tobacco-specific nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) and that the binucleated cells with micronuclei, nucleoplasmic bridges, and nuclear buds in lymphocytes (chromosome damage endpoints measured by the assay) are strong predictors of lung cancer risk. In the current study, we refined our analysis to include toxicity endpoints (micronuclei in mononucleated cells, apoptosis, necrosis, and nuclear division index) to investigate the benefit of including these variables on improving the predictive value of the assay. Baseline and NNK-induced micronuclei in mononucleated cells were significantly higher in patients (n = 139) than controls (n = 130; P < 0.001). Baseline apoptosis was higher among cases; however, the controls showed a significant higher fold increase in NNK-induced apoptosis compared with baseline (P < 0.001). Principal components analysis was used to derive a summary measure for all endpoints and calculate the positive predictive value (PPV) and negative predictive value (NPV) for disease status. First principal component for NNK-induced chromosome damage endpoints (binucleated cells with micronuclei, nucleoplasmic bridges, and nuclear buds) had an area under the curve = 97.9 (95% confidence interval, 95.9-99.0), PPV = 94.8, and NPV = 92.6. The discriminatory power improved when micronuclei in mononucleated cells were included: area under the curve = 99.1 (95% confidence interval, 97.9-100.0), PPV = 98.7 and NPV = 95.6. The simplicity, rapidity, and sensitivity of the assay together with potential for automation make it a valuable tool for screening and prioritizing potential cases for intensive screening. (Cancer Epidemiol Biomarkers Prev 2008;17(5):1111–9)

Magnesium (Mg) is required for maintenance of genomic stability; however, data on the relationship between dietary Mg intake and lung cancer are lacking. In an ongoing lung cancer case–control study, we identified 1139 cases and 1210 matched healthy controls with data on both diet and DNA repair capacity (DRC). Dietary intake was assessed using a modified Block-NCI food frequency questionnaire and DRC was measured using the host-cell reactivation assay to assess repair in lymphocyte cultures. After adjustment for potential confounding factors including DRC, the odds ratios (ORs) and 95% confidence intervals (CIs) for lung cancer with increasing quartiles of dietary Mg intake were 1.0, 0.83 (0.66–1.05), 0.64 (0.50–0.83) and 0.47 (0.36–0.61), respectively, for all subjects (P-trend < 0.0001). Similar results were observed by histology and clinical stage of lung cancer. Low dietary Mg intake was associated with poorer DRC and increased risk of lung cancer. In joint effects analyses, compared with those with high dietary Mg intake and proficient DRC, the OR (95% CI) for lung cancer in the presence of both low dietary Mg and suboptimal DRC was 2.36 (1.83–3.04). Similar results were observed for men and women. The effects were more pronounced among older subjects (>60 years), current or heavier smokers, drinkers, those with a family history of cancer in first-degree relatives, small cell lung cancer and late-stage disease. These intriguing results need to be confirmed in prospective studies.

Background : After a prolonged period of increasing rates of lung cancer incidence and mortality for both men and women, incidence and mortality rates are decreasing in men and stabilizing in women. The goal of this study was to assess changes over 20 years in the prevalence of known risk factors for lung cancer and to elucidate possible predictors associated with lung cancer survival. Methods : The study included a total of 908 patients with primary lung cancer referred to The University of Texas M.D. Anderson Cancer Center over three study periods 1985–1989 ( N =392), 1993–1997 ( N =216), and 2000–2004 ( N =300). Detailed questionnaires were used to collect information from the patients. Hazard ratios were estimated by fitting a Cox proportional hazards model. Using the Kaplan–Meier method, survival in months was calculated up to 2 years from the date of diagnosis to achieve comparability in the three groups. Results : We observed a decrease in the proportion of patients who are current cigarette smokers and an increase in the proportion of patients who present with adenocarcinoma of the lung, are obese and patients who present with localized disease. We also found an increase in the number of patients who report a family history of lung cancer. The overall median survival duration has increased over the years from 12.0 months in 1985–1989 to 17.5 months in 2000–2004. Also, the probability of survival of patients who were alive at 2 years after diagnosis has also increased (26.5% in 1985–1989 to 40.8% in 2000–2004). Overall, women had a better median survival than men. Conclusions : The results show that the demographic, histologic, clinical, and outcome variables of patients with lung cancer have changed over the past 20 years. Most important, the survival of patients with lung cancer has improved.

Background Reliable risk prediction tools for estimating individual probability of lung cancer have important public health implications. We constructed and validated a comprehensive clinical tool for lung cancer risk prediction by smoking status. Methods Epidemiologic data from 1851 lung cancer patients and 2001 matched control subjects were randomly divided into separate training (75% of the data) and validation (25% of the data) sets for never, former, and current smokers, and multivariable models were constructed from the training sets. The discriminatory ability of the models was assessed in the validation sets by examining the areas under the receiver operating characteristic curves and with concordance statistics. Absolute 1-year risks of lung cancer were computed using national incidence and mortality data. An ordinal risk index was constructed for each smoking status category by summing the odds ratios from the multivariable regression analyses for each risk factor. Results All variables that had a statistically significant association with lung cancer (environmental tobacco smoke, family history of cancer, dust exposure, prior respiratory disease, and smoking history variables) have strong biologically plausible etiologic roles in the disease. The concordance statistics in the validation sets for the never, former, and current smoker models were 0.57, 0.63, and 0.58, respectively. The computed 1-year absolute risk of lung cancer for a hypothetical male current smoker with an estimated relative risk close to 9 was 8.68%. The ordinal risk index performed well in that true-positive rates in the designated high-risk categories were 69% and 70% for current and former smokers, respectively. Conclusions If confirmed in other studies, this risk assessment procedure could use easily obtained clinical information to identify individuals who may benefit from increased screening surveillance for lung cancer. Although the concordance statistics were modest, they are consistent with those from other risk prediction models.

The group that formed on the theme of linkage analyses of rheumatoid arthritis RA and related phenotypes (Group 10) in the Genetic Analysis Workshop 15 comprised 18 sets of investigators. Two data sets were available: one was a real set provided by the North American Rheumatoid Arthritis Consortium and collaborators in Canada, France (European Consortium Of Rheumatoid Arthritis Families) and the UK; the other was a simulated data set modelled after the real data set. Whereas a majority of the investigators analyzed the RA affection status as a binary phenotype, a few contributions considered data on correlated quantitative traits such as anti-cyclic citrullinated peptide and rheumatoid factor-immunoglobulin M. The different investigators applied a wide spectrum of linkage methods. As expected, most methods could identify the human leukocyfeantigen region on chromosome 6 as a major genetic factor for RA. In addition, some novel chromosomal regions provided significant evidence of linkage in multiple contributions in the group. In this report, we discuss the different strategies explored by the different investigators with the common goal of improving the power to detect linkage.

Purpose: Accumulating evidence supports the contention that genetic variation is associated with neurocognitive function in healthy individuals and increased risk for neurocognitive decline in a variety of patient populations, including cancer patients. However, this has rarely been studied in glioma patients. Experimental Design: To identify the effect of genetic variants on neurocognitive function, we examined the relationship between the genotype frequencies of 10,967 single-nucleotide polymorphisms in 580 genes related to five pathways (inflammation, DNA repair, metabolism, cognitive, and telomerase) and neurocognitive function in 233 newly diagnosed glioma patients before surgical resection. Four neuropsychologic tests that measured memory (Hopkins Verbal Learning Test—Revised), processing speed (Trail Making Test A), and executive function (Trail Making Test B, Controlled Oral Word Association) were examined. Results: Eighteen polymorphisms were associated with processing speed and 12 polymorphisms with executive function. For processing speed, the strongest signals were in IRS1 rs6725330 in the inflammation pathway (P = 2.5 × 10−10), ERCC4 rs1573638 in the DNA repair pathway (P = 3.4 × 10−7), and ABCC1 rs8187858 in metabolism pathway (P = 6.6 × 10−7). For executive function, the strongest associations were in NOS1 rs11611788 (P = 1.8 × 10−8) and IL16 rs1912124 (P = 6.0 × 10−7) in the inflammation pathway, and POLE rs5744761 (P = 6.0 × 10−7) in the DNA repair pathway. Joint effect analysis found significant gene polymorphism-dosage effects for processing speed (Ptrend = 9.4 × 10−16) and executive function (Ptrend = 6.6 × 10−15). Conclusions: Polymorphisms in inflammation, DNA repair, and metabolism pathways are associated with neurocognitive function in glioma patients and may affect clinical outcomes. Clin Cancer Res; 21(14); 3340–6. ©2015 AACR.

Colorectal cancer (CRC) is a major cause of morbidity and mortality from cancers in the United States. The field of molecular epidemiology is in the forefront in the discovery of genes associated with the development and progression of complex diseases such as CRC, including hereditary CRC, and polyposis syndromes such as familial adenomatous polyposis and hereditary nonpolyposis colon cancer. Recent advances in laboratory methods (ie, high-throughput genotyping and high-density single nucleotide polymorphism chips, etc.) allow the molecular epidemiologist to elucidate biological determinates of disease. However, with these advancements in the lab, advances in modeling and testing of such data are needed as well. Herein, we review the current analytical methods that have been applied to molecular epidemiologic studies for CRC and hereditary nonpolyposis colon cancer within the past 2 years, comment on the application of these methods, and examine new and promising tools that will likely influence the discovery of gene-gene and gene-environment interactions and development of pathway-based analytical approaches for CRC risk and progression.

Zinc, copper and selenium are important cofactors for several enzymes that play a role in maintaining DNA integrity. However, limited epidemiologic research on these dietary trace metals and lung cancer risk is available. In an ongoing study of 1,676 incident lung cancer cases and 1,676 matched healthy controls, we studied the associations between dietary zinc, copper and selenium and lung cancer risk. Using multiple logistic regression analysis, the odds ratios (OR) and 95% confidence intervals (CI) of lung cancer for all subjects by increasing quartiles of dietary zinc intake were 1.0, 0.80 (0.65-0.99), 0.64 (0.51-0.81), 0.57 (0.42-0.75), respectively (p trend = 0.0004); similar results were found for men. For dietary copper, the ORs and 95% CI for all subjects were 1.0, 0.59 (0.49-0.73), 0.51 (0.41-0.64), 0.34 (0.26-0.45), respectively (p trend0.0001); similar reductions in risk and trend were observed by gender. Dietary selenium intake was not associated with risk, except for a significant inverse trend (p = 0.04) in men. Protective trends (p0.05) against lung cancer with increased dietary zinc intake were also found for all ages, BMI25, current smokers, pack-yearsor =30, light drinkers and participants without emphysema. Increased dietary copper intake was associated with protective trends (p0.05) across all ages, BMI, smoking and vitamin/mineral supplement categories, pack-yearsor =30 and 30.1-51.75 and participants without emphysema. Our results suggest that dietary zinc and copper intakes are associated with reduced risk of lung cancer. Given the known limitations of case-control studies, these findings must be interpreted with caution and warrant further investigation.

PurposeUnderstanding how specific genetic variants modify drug action pathways may provide informative blueprints for individualized chemotherapy.MethodsWe applied a pathway-based approach to examine the impact of a comprehensive panel of genetic polymorphisms on clinical outcomes in 210 esophageal cancer patients.ResultsIn the Cox proportional hazards model, MTHFR Glu429Ala variant genotypes were associated with significantly improved survival (hazard ratio [HR] = 0.56; 95% CI, 0.35 to 0.89) in patients treated with fluorouracil (FU). The 3-year survival rates for patients with the variant genotypes and the wild genotypes were 65.26% and 46.43%, respectively. Joint analysis of five polymorphisms in three FU pathway genes showed a significant trend for reduced recurrence risk and longer recurrence-free survival as the number of adverse alleles decreased (P = .004). For patients receiving platinum drugs, the MDR1 C3435T variant allele was associated with significantly reduced recurrence risk (HR = 0.25; 95% CI, 0.10 to 0.64) and improved survival (HR = 0.44; 95% CI, 0.23 to 0.85). In nucleotide excision repair genes, there was a significant trend for a decreasing risk of death with a decreasing number of high-risk alleles (P for trend = .0008). In base excision repair genes, the variant alleles of XRCC1 Arg399Gln were significantly associated with the absence of pathologic complete response (odds ratio = 2.75; 95% CI, 1.14 to 6.12) and poor survival (HR = 1.92; 95% CI, 1.00 to 3.72).ConclusionSeveral biologically plausible associations between individual single nucleotide polymorphisms and clinical outcomes were found. Our data also strongly suggest that combined pathway-based analysis may provide valuable prognostic markers of clinical outcomes.

In this case-control study, we modified the cytokinesis-block micronucleus (CBMN) assay, an established biomarker for genomic instability, to evaluate susceptibility to the nicotine-derived nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) by measuring the frequency of NNK-induced chromosomal damage endpoints (micronuclei, nucleoplasmic bridges, and nuclear buds) per 1,000 binucleated lymphocytes. Spontaneous and NNK-induced chromosomal damage were significantly higher in lung cancer patients compared with controls. Forty-seven percent of cases (versus 12% of controls) had ≥4 spontaneous micronuclei, 66% of cases (and no controls) had ≥4 spontaneous nucleoplasmic bridges, and 25% of cases (versus 5% of controls) had ≥1 spontaneous nuclear bud (P < 0.001). Similarly, 40% of cases (versus 6% of the controls) had ≥5 NNK-induced micronuclei, 89% of cases (and no controls) had ≥6 induced nucleoplasmic bridges, and 23% of cases (versus 2% of controls) had ≥2 induced nuclear buds (P < 0.001). When analyzed on a continuous scale, spontaneous micronuclei, nucleoplasmic bridges, and nuclear buds were associated with 2-, 29-, and 6-fold increases in cancer risk, respectively. Similarly, NNK-induced risks were 2.3-, 45.5-, and 10-fold, respectively. We evaluated the use of CBMN assay to predict cancer risk based on the numbers of micronuclei, nucleoplasmic bridges, and nuclear buds defined by percentile cut points in controls. Probabilities of being a cancer patient were 96%, 98%, and 100% when using the 95th percentiles of spontaneous and NNK-induced micronuclei, nucleoplasmic bridges, and nuclear buds, respectively. Our study indicates that the CBMN assay is extremely sensitive to NNK-induced genetic damage and may serve as a strong predictor of lung cancer risk. (Cancer Res 2006; 66(12): 6449-56)

Using cases from an ongoing case-control study, we completed a case series analysis by comparing epidemiologic, clinical and survival characteristics among lung cancer patients characterized by age at diagnosis. Our sample included 230 early onset lung cancer (EOLC) (all Caucasian and no older than 50 years of age at diagnosis) and 426 later-onset cases (LOLC) (all Caucasian and no younger than 70 years of age at diagnosis) who were referred to The University of Texas M.D. Anderson Cancer Center, Houston between 1995 and 2004. Detailed lifestyle, exposure, clinical, survival and self-reported cancer family history data were available from personal interviews. We observed a higher proportion of never smokers (23.9%) for the EOLC cases as compared to the LOLC cases (17.6%) and a higher proportion of former smokers (59.4%) among the LOLC cases compared to EOLC cases (17.8%). Adenocarcinoma was the most common histology (55.2%) among the EOLC cases. More (83.4%) of the EOLC cases presented with stage 3 or 4 lung cancer compared to the LOLC cases (58.6%). Median (M) survival was 16.7 months among the EOLC cases (M = 19.2 months for the LOLC cases) and the 24-month survival rate was 20.6% for the EOLC cases and 29.5% for the LOLC cases. Female EOLC cases (M = 20.7 months) exhibited better survival than male EOLC cases (M = 13.0 months, P = 0.004). EOLC cases diagnosed with squamous cell carcinoma had poorer survival (M = 8.2 months) compared to cases with other histologies (P0.001). For both groups, higher stage at presentation was associated with poorer survival (P0.001). These findings support the need for further study in the characterization and identification of genetic factors that influence and modulate early onset lung cancer risk and outcome.

Meta-analysis is being increasingly used as a tool for integrating data from different studies of complex phenotypes, because the power of any one study to identify causal loci is limited. We applied a novel meta-analytical approach (Loesgen et al. in Genet Epidemiol 21(Suppl 1):S142–S147, 2001) in compiling results from four studies of rheumatoid arthritis in Caucasians including two studies from NARAC (Jawaheer et al. in Am J Hum Genet 68:927–936, 2001; Jawaheer et al. in Arthritis Rheum 48:906–916, 2003), one study from the UK (MacKay et al. in Arthritis Rheum 46:632–639, 2001) and one from France (Cornelis et al. in Proc Natl Acad Sci USA 95:10746–10750, 1998). For each study, we obtained NPL scores by performing interval mapping (2 cM intervals) using GeneHunter2 (Kruglyak et al. in Am J Hum Genet 58:1347–1363, 1996; Markianos et al. in Am J Hum Genet 68:963–977, 2001). The marker maps differed among the three consortium groups, therefore, the marker maps were aligned after the interval mapping was completed and the NPL scores that were within 1 cM of each other were combined using the method of Loesgen et al. (Genet Epidemiol 21(Suppl 1):S142–S147, 2001) by calculating the weighted average of the NPL score. This approach avoids some problems in analysis encountered by using GeneHunter2 when some markers in the sample are not genotyped. This procedure provided marginal evidence (P

The candidate-gene approach in association studies of polygenic diseases has often yielded conflicting results. In this hospital-based case-control study with 696 white patients newly diagnosed with bladder cancer and 629 unaffected white controls, we applied a multigenic approach to examine the associations with bladder cancer risk of a comprehensive panel of 44 selected polymorphisms in two pathways, DNA repair and cell-cycle control, and to evaluate higher-order gene-gene interactions, using classification and regression tree (CART) analysis. Individually, only XPD Asp312Asn, RAG1 Lys820Arg, and a p53 intronic SNP exhibited statistically significant main effects. However, we found a significant gene-dosage effect for increasing numbers of potential high-risk alleles in DNA-repair and cell-cycle pathways separately and combined. For the nucleotide-excision repair pathway, compared with the referent group (fewer than four adverse alleles), individuals with four (odds ratio [OR] = 1.52, 95% CI 1.05–2.20), five to six (OR = 1.81, 95% CI 1.31–2.50), and seven or more adverse alleles (OR = 2.50, 95% CI 1.69–3.70) had increasingly elevated risks of bladder cancer (P for trend

Self-rated health (SRH), a consistent predictor of mortality among diverse populations, is sensitive to health indicators and social factors. American-born Hispanics report better SRH than their foreign-born counterparts but simultaneously report poorer health indicators and have shorter life expectancy. Using a matched prospective cross-sectional design, we analyzed data from 631 age-matched pairs of women, born in the United States or Mexico, enrolled in a cohort study based in Houston, Texas. Our first goal was to describe the relationships between SRH and health behaviors, physician-diagnosed chronic conditions, acculturation, and socioeconomic status (SES) by birthplace. Our second goal was to investigate the relative influence of SES, acculturation, health behaviors, and physician-diagnosed conditions in explaining expected differences in SRH between the two groups. Number of chronic conditions reported, particularly depression, more strongly influenced SRH than SES, acculturation, or reported health risk behaviors and the influence of birthplace is accounted for by these factors.

BACKGROUND. The familial risk of bladder cancer (BC) is not well understood and, to date, little attention has been paid to the joint effect of smoking and family history in modifying the risk of BC. The authors investigated the role of family history in association with the risk of BC. METHODS. Case and control probands were identified as part of an on-going BC case–control study. The relative risk associated with a family history of BC was estimated. RESULTS. In total, 713 cases and 658 controls were included. In a case–control analysis, compared with individuals who never smoked and who had no family history of BC, probands who had smoked and who also had a positive family history were at 5.31-fold increased risk of BC (P for interaction = .04). The 713 case probands and the 658 controls reported 5160 and 4816 first-degree relatives, respectively. Compared with never-smoking relatives who had probands diagnosed with BC at an older age (age >65 years), ever-smoking relatives who had probands diagnosed at a younger age (ages 40–65 years) showed a 6.89-fold (95% confidence interval, from 2.25-fold to 21.12-fold) increased risk. Similar results were obtained for the joint effects of family history of BC and smoking. CONCLUSIONS. The current results indicated that a positive family history of BC may have interacted with smoking habits to increase the risk of BC in the study population. Cancer 2006. © 2006 American Cancer Society.

BACKGROUND The objective of this study was to evaluate the effects of polymorphisms in 2 genes in the glutathione S-transferase (GST) family and the mutagen-sensitivity phenotype on the risk of second primary tumors (SPTs) in patients with previously diagnosed early-stage head and neck squamous cell carcinoma. Data were available for 303 patients who were enrolled in a placebo-controlled chemoprevention trial of low-dose 13-cis-retinoic acid to reduce the occurrence of SPTs. METHODS A Cox proportional hazards model and survival tree analysis were used to evaluate the association between specified genetic variations and the development of SPTs. The average number of bleomycin-induced chromatid breaks per cell was used to quantify mutagen sensitivity as an individual patient's degree of sensitivity to genotoxicity. RESULTS The GST-M1 null genotype was associated with an increased risk for any SPTs (hazard ratio [HR], 1.99; 95% confidence interval [95% CI], 1.11-3.56) and for tobacco-related SPTs (HR, 2.16; 95% CI, 1.01-4.62) after adjusting for covariates. The GST-T1 null genotype and bleomycin-induced chromatid breaks were not associated with a statistically significant increased risk for SPTs or tobacco-related SPTs after similar adjustment. Simultaneous nonnull status for both GST genotypes was associated with a decreased risk for any SPTs (HR, 0.52; 95% CI, 0.28-0.96) and tobacco-related SPTs (HR, 0.50; 95% CI, 0.22-1.11) compared with null status for GST-M1 accompanied by nonnull status for GST-T1. CONCLUSIONS An association was observed between the development of SPTs and the GST-M1 null genotype after successful treatment for early-stage head and neck squamous cell carcinoma. The GST-T1 null genotype and bleomycin-induced chromatid breaks were not associated with an increased risk, and no significant interactions were identified. Cancer 2006. © 2006 American Cancer Society.

Objective HLA is the most strongly associated locus in rheumatoid arthritis (RA), accounting for up to one-third of the genetic contribution. Conditioning on the effect of true disease loci such as HLA can lead to increased power to detect effects at other loci and, in addition, allows investigation of the underlying disease models, including interactions. The aim of this study was to detect susceptibility loci for RA by conditioning on HLA in a large sample of affected sibling pairs (ASPs) and to test for evidence of interaction between novel loci and HLA. Methods Genotype data from 3 whole-genome linkage scans for RA in a US population and a UK population were pooled, resulting in a combined data set of 886 ASPs. This pooling of data increased the power to detect loci showing low levels of heterogeneity. Nonparametric linkage analysis was performed to identify regions of interest. Joint 2-locus analysis was then performed for HLA and each of the loci that demonstrated evidence of linkage in the 886 ASPs. Results Evidence for linkage was most significant at HLA (P = 4 × 10−16), with 7 non-HLA loci showing some evidence for linkage (P = 0.05–0.003). Joint modeling of these loci with HLA provided evidence for linkage at a genome-wide significance level for loci on 6q (P = 2.7 × 10−6) and 16p (P = 2 × 10−4). Conclusion These data provide the most convincing evidence to date that 6q and 16p harbor susceptibility genes. In addition, these loci may interact with HLA, facilitating the search for candidate genes within this region.

Variance components analysis provides an efficient method for performing linkage analysis for quantitative traits. However, power and type 1 error of variance components-based likelihood ratio testing may be affected when phenotypic data are nonnormally distributed (especially with high values of kurtosis) and there is moderate to high correlation among the siblings. Winsorization can reduce the effect of outliers on statistical analyses. Here, we considered the effect of winsorization on variance components-based tests. We considered the likelihood ratio test (LRT), the Wald test, and some robust variance components tests. We compared these tests with Haseman-Elston least squares-based tests. We found that power to detect linkage is significantly increased after winsorization of the nonnormal phenotypes. Winsorization does not greatly diminish the type 1 error for the variance components-based tests for markedly nonnormal data. A robust version of the LRT that adjusts for sample kurtosis showed the best power for nonnormal data. Finally, phenotype winsorization of nonnormal data reduces the bias in estimation of the major gene variance component.

Objective A number of non-HLA loci that have shown evidence (P < 0.05) for linkage with rheumatoid arthritis (RA) have been previously identified. The present study attempts to confirm these findings. Methods We performed a second genome-wide screen of 256 new multicase RA families recruited from across the United States by the North American Rheumatoid Arthritis Consortium. Affected sibling pair analysis on the new data set was performed using SIBPAL. We subsequently combined our first and second data sets in an attempt to enhance the evidence for linkages in a larger sample size. We also evaluated the impact of covariates on the support for linkage, using LODPAL. Results Evidence of linkage at 1p13 (D1S1631), 6p21.3 (the HLA complex), and 18q21 (D18S858) (P < 0.05) was replicated in this independent data set. In addition, there was new evidence for linkage at 9p22 (D9S1121 [P = 0.001]) and 10q21 (D10S1221 [P = 0.0002] and D10S1225 [P = 0.0038]) in the current data set. The combined analysis of both data sets (512 families) showed evidence for linkage at the level of P < 0.005 at 1p13 (D1S1631), 1q43 (D1S235), 6q21 (D6S2410), 10q21 (D10S1221), 12q12 (D12S398), 17p13 (D17S1298), and 18q21 (D18S858). Linkage at HLA was also confirmed (P < 5 × 10−12). Inclusion of DRB1∗04 as a covariate significantly increased the probability of linkage on chromosome 6. In addition, some linkages on chromosome 1 showed improved significance when modeling DRB1∗04 or rheumatoid factor positivity as covariates. Conclusion These results provide a rational basis for pursuing high-density linkage and association studies of RA in several regions outside of the HLA region, particularly on chromosomes 1p, 1q, and 18q.

Non-normality of the phenotypic distribution can affect power to detect quantitative trait loci in sib pair studies. Previously, we observed that Winsorizing the sib pair phenotypes increased the power of quantitative trait locus (QTL) detection for both Haseman-Elston (HE) least-squares tests [Hum Hered 2002;53:59–67] and maximum likelihood-based variance components (MLVC) analysis [Behav Genet (in press)]. Winsorizing the phenotypes led to a slight increase in type 1 error in H-E tests and a slight decrease in type I error for MLVC analysis. Herein, we considered transforming the sib pair phenotypes using the Box-Cox family of transformations. Data were simulated for normal and non-normal (skewed and kurtic) distributions. Phenotypic values were replaced by Box-Cox transformed values. Twenty thousand replications were performed for three H-E tests of linkage and the likelihood ratio test (LRT), the Wald test and other robust versions based on the MLVC method. We calculated the relative nominal inflation rate as the ratio of observed empirical type 1 error divided by the set α level (5, 1 and 0.1% α levels). MLVC tests applied to non-normal data had inflated type I errors (rate ratio greater than 1.0), which were controlled best by Box-Cox transformation and to a lesser degree by Winsorizing. For example, for non-transformed, skewed phenotypes (derived from a χ2 distribution with 2 degrees of freedom), the rates of empirical type 1 error with respect to set α level = 0.01 were 0.80, 4.35 and 7.33 for the original H-E test, LRT and Wald test, respectively. For the same α level = 0.01, these rates were 1.12, 3.095 and 4.088 after Winsorizing and 0.723, 1.195 and 1.905 after Box-Cox transformation. Winsorizing reduced inflated error rates for the leptokurtic distribution (derived from a Laplace distribution with mean 0 and variance 8). Further, power (adjusted for empirical type 1 error) at the 0.01 α level ranged from 4.7 to 17.3% across all tests using the non-transformed, skewed phenotypes, from 7.5 to 20.1% after Winsorizing and from 12.6 to 33.2% after Box-Cox transformation. Likewise, power (adjusted for empirical type 1 error) using leptokurtic phenotypes at the 0.01 α level ranged from 4.4 to 12.5% across all tests with no transformation, from 7 to 19.2% after Winsorizing and from 4.5 to 13.8% after Box-Cox transformation. Thus the Box-Cox transformation apparently provided the best type 1 error control and maximal power among the procedures we considered for analyzing a non-normal, skewed distribution (χ2) while Winzorizing worked best for the non-normal, kurtic distribution (Laplace). We repeated the same simulations using a larger sample size (200 sib pairs) and found similar results.

Background: Occupational asbestos exposure has been found to increase lung cancer risk in epidemiologic studies. Methods: We conducted an asbestos exposure–gene interaction analyses among several Caucasian populations who were current or ex-smokers. The discovery phase included 833 Caucasian cases and 739 Caucasian controls, and used a genome-wide association study (GWAS) to identify single-nucleotide polymorphisms (SNP) with gene–asbestos interaction effects. The top ranked SNPs from the discovery phase were replicated within the International Lung and Cancer Consortium (ILCCO). First, in silico replication was conducted in those groups that had GWAS and asbestos exposure data, including 1,548 cases and 1,527 controls. This step was followed by de novo genotyping to replicate the results from the in silico replication, and included 1,539 cases and 1,761 controls. Multiple logistic regression was used to assess the SNP–asbestos exposure interaction effects on lung cancer risk. Results: We observed significantly increased lung cancer risk among MIRLET7BHG (MIRLET7B host gene located at 22q13.31) polymorphisms rs13053856, rs11090910, rs11703832, and rs12170325 heterozygous and homozygous variant allele(s) carriers (P < 5 × 10−7 by likelihood ratio test; df = 1). Among the heterozygous and homozygous variant allele(s) carriers of polymorphisms rs13053856, rs11090910, rs11703832, and rs12170325, each unit increase in the natural log-transformed asbestos exposure score was associated with age-, sex-, smoking status, and center-adjusted ORs of 1.34 [95% confidence interval (CI), 1.18–1.51], 1.24 (95% CI, 1.14–1.35), 1.28 (95% CI, 1.17–1.40), and 1.26 (95% CI, 1.15–1.38), respectively, for lung cancer risk. Conclusion: Our findings suggest that MIRLET7BHG polymorphisms may be important predictive markers for asbestos exposure–related lung cancer. Impact: To our knowledge, our study is the first report using a systematic genome-wide analysis in combination with detailed asbestos exposure data and replication to evaluate asbestos-associated lung cancer risk. Cancer Epidemiol Biomarkers Prev; 24(10); 1564–73. ©2015 AACR.

An attractive feature of variance-components methods (including the Haseman-Elston tests) for the detection of quantitative-trait loci (QTL) is that these methods provide estimates of the QTL effect. However, estimates that are obtained by commonly used methods can be biased for several reasons. Perhaps the largest source of bias is the selection process. Generally, QTL effects are reported only at locations where statistically significant results are obtained. This conditional reporting can lead to a marked upward bias. In this article, we demonstrate this bias and show that its magnitude can be large. We then present a simple method-of-moments (MOM)–based procedure to obtain more-accurate estimates, and we demonstrate its validity via Monte Carlo simulation. Finally, limitations of the MOM approach are noted, and we discuss some alternative procedures that may also reduce bias.

Background: There is an urgent need to improve lung cancer outcome by identifying and validating markers of risk. We previously reported that the cytokinesis-blocked micronucleus assay (CBMN) is a strong predictor of lung cancer risk. Here, we validate our findings in an independent external lung cancer population and test discriminatory power improvement of the Spitz risk prediction model upon extension with this biomarker. Methods: A total of 1,506 participants were stratified into a test set of 995 (527 cases/468 controls) from MD Anderson Cancer Center (Houston, TX) and a validation set of 511 (239 cases/272 controls) from Massachusetts General Hospital (Boston, MA). An epidemiologic questionnaire was administered and genetic instability was assessed using the CBMN assay. Results: Excellent concordance was observed between the two populations in levels and distribution of CBMN endpoints [binucleated-micronuclei (BN-MN), binucleated-nucleoplasmic bridges (BN-NPB)] with significantly higher mean BN-MN and BN-NPB values among cases (P < 0.0001). Extension of the Spitz model led to an overall improvement in the AUC (95% confidence intervals) from 0.61 (55.5–65.7) with epidemiologic variables to 0.92 (89.4–94.2) with addition of the BN-MN endpoint. The most dramatic improvement was observed with the never-smokers extended model followed by the former and current smokers. Conclusions: The CBMN assay is a sensitive and specific predictor of lung cancer risk, and extension of the Spitz risk prediction model led to an AUC that may prove useful in population screening programs to identify the “true” high-risk individuals. Impact: Identifying high-risk subgroups that would benefit from screening surveillance has immense public health significance. Cancer Epidemiol Biomarkers Prev; 23(11); 2462–70. ©2014 AACR.

Preimplantation genetic diagnosis (PGD) allows couples to avoid having a child with an inherited condition, potentially reducing cancer burden in families with a hereditary cancer predisposition. This study investigated and compared awareness and acceptance of PGD among patients with different hereditary cancer syndromes. Questionnaires were mailed to 984 adults with hereditary breast and ovarian cancer, Lynch syndrome, familial adenomatous polyposis, or multiple endocrine neoplasia type 1 or 2. Associations between clinical, demographic, and psychosocial factors and awareness and acceptance of PGD were examined. Of 370 respondents (38 % return rate), 28 % felt their syndrome impacted family planning, 24 % were aware of PGD, 72 % felt that PGD should be offered, 43 % would consider using PGD, and 29 % were uncertain. Family experience and syndrome-specific characteristics, such as disease severity, quality of life and availability of medical interventions as well as gender, family planning stage, and religiosity impact perceptions of the acceptability of PGD, though a high level of uncertainty exists. Hereditary cancer patients lack awareness of PGD despite feeling that PGD should be offered, highlighting the need for education on this topic. While we found attitudes about the acceptability of PGD to be generally similar to those reported in the literature and of genetics and ethics experts, we observed similarities and differences between syndromes that provide insight into why some hereditary cancer patients may find PGD more acceptable than others.

We report results using a new meta-analysis procedure to assess linkage of immunoglobulin E (IgE), an asthma related quantitative trait, using the nine data sets provided by the Genetic Analysis Workshop 12. This meta-analysis procedure combines univariate Haseman-Elston statistics across studies gaining strength by collating possibly distinct marker maps. We performed univariate Haseman-Elston over all data sets and identified linkage (p < 0.05) to some marker in at least one study on virtually every chromosome. Using the proposed meta-analysis procedure, we detected suggestive linkage (p-value < 7.4 x 10(-4), [Lander and Kruglyak, Nat Genet 11:214-47, 1995]) for two regions on chromosome 4 (around 50 and 150 cM) and one region on chromosome 11 (around 125 cM). We also identified areas which were evocative (p-value < 0.02) for linkage: chr 5-40 cM, chr 7-98 cM, chr 9-65 cM, chr 13-110 cM, chr 16-10 cM and approximately 105 cM, chr 17-70 cM, and chr 20-25 cM.

Several meta-analytic techniques have been developed for combining information from multiple studies in contexts other than linkage detection. We apply the technique of combining parameter estimates to the problem of finding disease loci in the simulated data and compare results with those obtained by reanalyzing pooled raw data. To facilitate the combination of study results, we highly recommend that parameter estimates and their standard errors be reported in published studies. If different research groups were to make original data available, progress toward disease gene location and characterization may be more quickly made.

Meta-analysis has been little explored to make an overall assessment of linkage from different studies. In practice, it is likely that published linkage studies will only report p-values. We compared the performance of the widely used Fisher method for combining p-values with that of pooling raw data. More loci were consistently found by pooling raw data. In the absence of further information, combining p-values can provide an overall, but limited, assessment of different linkage studies. However, meta-analysis would be better viewed as a preliminary step toward the goal of analyzing the pooled raw data.