Population Substructure and Control Selection in Genome-Wide Association Studies

Determination of the relevance of both demanding classical epidemiologic criteria for control selection and robust handling of population stratification (PS) represents a major challenge in the design and analysis of genome-wide association studies (GWAS). Empirical data from two GWAS in European Americans of the Cancer Genetic Markers of Susceptibility (CGEMS) project were used to evaluate the impact of PS in studies with different control selection strategies. In each of the two original case-control studies nested in corresponding prospective cohorts, a minor confounding effect due to PS (inflation factor λ of 1.025 and 1.005) was observed. In contrast, when the control groups were exchanged to mimic a cost-effective but theoretically less desirable control selection strategy, the confounding effects were larger (λ of 1.090 and 1.062). A panel of 12,898 autosomal SNPs common to both the Illumina and Affymetrix commercial platforms and with low local background linkage disequilibrium (pair-wise r2<0.004) was selected to infer population substructure with principal component analysis. A novel permutation procedure was developed for the correction of PS that identified a smaller set of principal components and achieved a better control of type I error (to λ of 1.032 and 1.006, respectively) than currently used methods. The overlap between sets of SNPs in the bottom 5% of p-values based on the new test and the test without PS correction was about 80%, with the majority of discordant SNPs having both ranks close to the threshold. Thus, for the CGEMS GWAS of prostate and breast cancer conducted in European Americans, PS does not appear to be a major problem in well-designed studies. A study using suboptimal controls can have acceptable type I error when an effective strategy for the correction of PS is employed

Determinants of leptospirosis in Sri Lanka: Study Protocol

<p>Abstract</p> <p>Background</p> <p>Leptospirosis is becoming a major public health threat in Sri Lanka as well as in other countries. We designed a case control study to determine the factors associated with local transmission of leptospirosis in Sri Lanka, in order to identify major modifiable determinants of leptospirosis. The purpose of this paper is to describe the study protocol in detail prior to the publishing of the study results, so that the readership will be able to understand and interpret the study results effectively.</p> <p>Methods</p> <p>A hospital based partially matched case control design is proposed. The study will be conducted in three selected leptospirosis endemic districts in central Sri Lanka. Case selection will include screening all acute fever patients admitted to selected wards to select probable cases of leptospirosis and case confirmation using an array of standard laboratory criteria. Age and sex matched group of acute fever patients with other confirmed diagnosis will be used as controls. Case to control ratio will be 1:2. A minimum sample of 144 cases is required to detect 20% exposure with 95% two sided confidence level and 80% power. A pre tested interviewer administered structured questionnaire will be used to collect data from participants. Variables included in the proposed study will be evaluated using conceptual hierarch of variables in three levels; Exposure variables as proximal; reservoir and environmental variables as intermediate; socio-demographic variables as distal. This conceptual hierarch hypothesised that the distal and intermediate variables are mediated through the proximal variables but not directly. A logistic regression model will be used to analyse the probable determinants of leptospirosis. This model will evaluate the effect of same level and upper level variables on the outcome leptospirosis, using three blocks.</p> <p>Discussion</p> <p>The present national control programme of leptospirosis is hampered by lack of baseline data on leptospirosis disease transmission. The present study will be able to provide these essential information for formulation of better control strategies.</p

A Case-Control Study of Peripheral Blood Mitochondrial DNA Copy Number and Risk of Renal Cell Carcinoma

Background: Low mitochondrial DNA (mtDNA) copy number is a common feature of renal cell carcinoma (RCC), and may influence tumor development. Results: from a recent case-control study suggest that low mtDNA copy number in peripheral blood may be a marker for increased RCC risk. In an attempt to replicate that finding, we measured mtDNA copy number in peripheral blood DNA from a U.S. population-based case-control study of RCC. Methodology/Principal Findings: Relative mtDNA copy number was measured in triplicate by a quantitative real-time PCR assay using DNA extracted from peripheral whole blood. Cases (n = 603) had significantly lower mtDNA copy number than controls (n = 603; medians 0.85, 0.91 respectively; P = 0.0001). In multiple logistic regression analyses, the lowest quartile of mtDNA copy number was associated with a 60% increase in RCC risk relative to the highest quartile (OR = 1.6, 95% CI = 1.1–2.2; Ptrend = 0.009). This association remained in analyses restricted to cases treated by surgery alone (OR Q1 = 1.4, 95% CI = 1.0–2.1) and to localized tumors (2.0, 1.3–2.8). Conclusions/Significance: Our findings from this investigation, to our knowledge the largest of its kind, offer important confirmatory evidence that low mtDNA copy number is associated with increased RCC risk. Additional research is needed to assess whether the association is replicable in prospective studies

Risk of renal cell carcinoma in relation to blood telomere length in a population-based case–control study

Background: There are few known risk factors for renal cell carcinoma (RCC). Two small hospital-based case–control studies suggested an association between short blood telomere length (TL) and increased RCC risk. Methods: We conducted a large population-based case–control study in two metropolitan regions of the United States comparing relative TL in DNA derived from peripheral blood samples from 891 RCC cases and 894 controls. Odds ratios and 95% confidence intervals were estimated using unconditional logistic regression in both unadjusted and adjusted models. Results: Median TL was 0.85 for both cases and controls (P=0.40), and no differences in RCC risk by quartiles of TL were observed. Results of analyses stratified by age, sex, race, tumour stage, and time from RCC diagnosis to blood collection were similarly null. In multivariate analyses among controls, increasing age and history of hypertension were associated with shorter TL (P<0.001 and P=0.07, respectively), and African Americans had longer TL than Caucasians (P<0.001). Conclusion: These data do not support the hypothesis that blood TL is associated with RCC. This population-based case–control study is, to our knowledge, the largest investigation to date of TL and RCC

Colon cancer controls versus population controls in case-control studies of occupational risk factors

BACKGROUND: Since updated population registers do not exist in many countries it is often difficult to sample valid population controls from the study base to a case-control study. Use of patient controls is an alternative option if the exposure experience under study for these patients are interchangeable with the experience for population controls. Patient controls may even be preferable from population controls under certain conditions. In this study we examine if colon cancer patients can serve as surrogates for proper population controls in case-control studies of occupational risk factors. METHODS: The study was conducted from 1995 to 1997. Incident colon cancer controls (N = 428) aged 35–69 years with a histological verified diagnosis and population controls (N = 583) were selected. Altogether 254 (59%) of the colon cancer controls and 320 (55%) of the population controls were interviewed about occupational, medical and life style conditions. RESULTS: No statistical significant difference for educational level, medical history or smoking status was seen between the two control groups. There was evidence of a higher alcohol intake, less frequent work as a farmer and less exposure to pesticides among colon cancer controls. CONCLUSIONS: Use of colon cancer controls may provide valid exposure estimates in studies of many occupational risk factors for cancer, but not for studies on exposure related to farming

The Chernobyl childhood leukemia study: background & lessons learned

Many challenges emerged during completion of a study to examine radiation dose and acute leukemia among children in areas of the former Soviet Union. In an era of globalization, our experiences might benefit others involved in multinational investigations

An invitation to grieve: reconsidering critical incident responses by support teams in the school setting

This paper proposes that consideration could be given to an invitational intervention rather than an expectational intervention when support personnel respond to a critical incident in schools. Intuitively many practitioners know that it is necessary for guidance/counselling personnel to intervene in schools in and following times of trauma. Most educational authorities in Australia have mandated the formulation of a critical incident intervention plan. This paper defines the term critical incident and then outlines current intervention processes, discussing the efficacy of debriefing interventions. Recent literature suggests that even though it is accepted that a planned intervention is necessary, there is scant evidence as to the effectiveness of debriefing interventions in stemming later symptoms of post traumatic stress disorder. The authors of this paper advocate for an expressive therapy intervention that is invitational rather than expectational, arguing that not all people respond to trauma in the same way and to expect that they will need to recall and retell what has happened is most likely a dangerous assumption. A model of invitation using Howard Gardner’s (1983) multiple intelligences is proposed so that students are invited to grieve and understand emotionally what is happening to them following a critical incident

The polyAT, intronic IVS11-6 and Lys939Gln XPC polymorphisms are not associated with transitional cell carcinoma of the bladder

Chemical carcinogens from cigarette smoking and occupational exposure are risk factors for bladder transitional cell carcinoma (TCC). The Xeroderma Pigmentosum Group C (XPC) gene is essential for repair of bulky adducts from carcinogens. The Xeroderma Pigmentosum Group C gene polymorphisms may alter DNA repair capacity (DRC), thus giving rise to genetic predisposition to bladder cancer. Recent studies have demonstrated linkage disequilibrium between three polymorphisms in the XPC gene (polyAT, IVS11-6 and Lys939Gln) and these have been shown to influence the DRC, as well as to be associated with bladder cancer risk. We analysed all three XPC polymorphisms in 547 bladder TCC patients and 579 cancer-free controls to investigate the association between these polymorphisms and bladder cancer susceptibility, and we also attempted to assess gene–environmental interactions. We confirmed strong linkage disequilibrium among the polymorphisms (Lewontin's D′>0.99). Using logistic regression adjusting for smoking, occupational and family history, neither the heterozygote nor the homozygote variants of these polymorphisms were associated with increased bladder cancer risk (adjusted odds ratio [95% confidence interval] for heterozygote 0.82 [0.63–1.07], 0.82 [0.63–1.08] and 0.83 [0.63–1.08] for PolyAT, IVS11-6 and Lys939Gln, respectively and homozygote variant, 0.98 [0.68–1.42], 0.99 [0.69–1.43] and 1.01 [0.70–1.46]). Moreover, we did not find any significant interaction between these XPC polymorphisms and environmental exposure to cigarette smoking and occupational carcinogens

A Bayesian method for evaluating and discovering disease loci associations

Background: A genome-wide association study (GWAS) typically involves examining representative SNPs in individuals from some population. A GWAS data set can concern a million SNPs and may soon concern billions. Researchers investigate the association of each SNP individually with a disease, and it is becoming increasingly commonplace to also analyze multi-SNP associations. Techniques for handling so many hypotheses include the Bonferroni correction and recently developed Bayesian methods. These methods can encounter problems. Most importantly, they are not applicable to a complex multi-locus hypothesis which has several competing hypotheses rather than only a null hypothesis. A method that computes the posterior probability of complex hypotheses is a pressing need. Methodology/Findings: We introduce the Bayesian network posterior probability (BNPP) method which addresses the difficulties. The method represents the relationship between a disease and SNPs using a directed acyclic graph (DAG) model, and computes the likelihood of such models using a Bayesian network scoring criterion. The posterior probability of a hypothesis is computed based on the likelihoods of all competing hypotheses. The BNPP can not only be used to evaluate a hypothesis that has previously been discovered or suspected, but also to discover new disease loci associations. The results of experiments using simulated and real data sets are presented. Our results concerning simulated data sets indicate that the BNPP exhibits both better evaluation and discovery performance than does a p-value based method. For the real data sets, previous findings in the literature are confirmed and additional findings are found. Conclusions/Significance: We conclude that the BNPP resolves a pressing problem by providing a way to compute the posterior probability of complex multi-locus hypotheses. A researcher can use the BNPP to determine the expected utility of investigating a hypothesis further. Furthermore, we conclude that the BNPP is a promising method for discovering disease loci associations. © 2011 Jiang et al