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Statistical Package (statistical + package)
Selected AbstractsEndonasal Endoscopic Management of Contact Point Headache and Diagnostic CriteriaHEADACHE, Issue 2 2010Alireza Mohebbi MD (Headache 2010;50:242-248) Background., Some types of headaches with sinonasal origin may be present in the absence of inflammation and infection. The contact points between the lateral nasal wall and the septum could be the cause of triggering and sustained pain via trigeminovascular system. Objective., The aim of this study was to evaluate the feasibility and effectiveness of endoscopic surgery in the sinonasal region for treatment of headache with special attention paid to specific diagnostic methods and patient selection. Methods., This was a prospective, non-randomized and semi-quasi experimental research study. Thirty-six patients with chronic headaches who had not previously responded to conventional treatments were evaluated by rhinoscopy and/or endoscopy, local anesthetic tests and computed tomography scans as diagnostic criteria. These patients were divided into 4 groups based on the diagnostic methods utilized. The intensity of headaches pre- and post-operatively were recorded by utilizing the visual analog scale scale and performing analysis with analysis of variance test comparison and Statistical Package for Social Sciences. Average follow-up was 30 months. Results., Our overall success rate approximated 83% while the complete cure rate was 11%. Patients in group 4 achieved the best results. In this group all diagnostic criteria were positive. In addition, patient responses were statistically significant in groups with more than one positive criteria compared with group 1 who only had positive examination. The positive response of 14 migrainous patients diagnosed with migraine prior to treatment was 64%. Conclusion., Surgery in specific cases of headaches with more positive evidence of contact point could be successful, particularly if medical therapy has failed. [source] Factors associated with the coping of parents with a child in psychiatric inpatient careINTERNATIONAL JOURNAL OF NURSING PRACTICE, Issue 5 2001Tiina Puotiniemi MSc The purpose of this study was to establish the parental coping' factors associated with having a child in psychiatric inpatient care. The data were collected from 19 hospitals with child psychiatry units. At the time of data collection, all parents of children in psychiatric inpatient care in these hospitals were recruited. The method of data collection was a questionnaire (n = 79). The data were analysed with the Statistical Package for the Social Sciences (SPSS) for Windows statistical software. The connections between variables were studied with cross-tabulation, and the ,2 test was used to determine significance. Changes in internal and external family relationships and matters related to the upbringing of the child with mental problems statistically correlated significantly with parental coping (P < 0.001). Problem-oriented and emotionally-oriented coping strategies, skills and palliative strategies correlated significantly with parental coping (P < 0.001). Emotional support, support for the care and upbringing of the child in inpatient care, and love and acceptance also had statistically significant associations with parental coping (P < 0.001). [source] Predictors of disability among Filipinos with knee osteoarthritisINTERNATIONAL JOURNAL OF RHEUMATIC DISEASES, Issue 3 2008Ester G. Penserga Abstract Aims: This study aims to describe the level of disability of Filipino patients with knee osteoarthritis (OA) in relation to common risk factors. Methodology: This is a cross-sectional analytic study. Patients with knee osteoarthritis diagnosed using the American College of Rheumatology criteria for the classification of knee OA, seen at East Avenue Medical Center, using the Quezon City, Philippines, were entered by convenient sampling. The Western Ontario and McMaster Universities (WOMAC (va) 3.1 Tagalog Version) osteoarthritis index was used. Self-reported disability was measured by the function subscale of the WOMAC OA index and used as the dependent variable. Independent variables assessed as possible risk factors affecting disability were age, sex, weight, height, body mass index (BMI), education (in years), number of comorbidities present, smoking status (pack years), duration of knee OA, pain and stiffness. Categories of disability were identified as high, moderate and low. Analyses of the data were performed using Statistical Package for the Social Sciences (SPSS) version 13. Results: Eighty-five subjects were included in the study. The mean disability score was 674.1 ± 318.81 (moderate disability). Chi-square tests showed that the categories or levels of disability are not significantly dependent on the categorical variables. Significant direct correlations were seen between mean disability and weight (r = 0.260, P = 0.016), pain (r = 0.574, P = 0.000), and stiffness (r = 0.616, P = 0.000). Conclusion: This is the first study analysing the relationship between disability and specific risk factors among Filipino patients with knee OA. Self-reported disability of knee OA in the population studied was strongly related to pain scores, weight and joint stiffness scores. [source] Subjective side effects of antipsychotics and medication adherence in people with schizophreniaJOURNAL OF ADVANCED NURSING, Issue 3 2009Terence V. McCann Abstract Title., Subjective side effects of antipsychotics and medication adherence in people with schizophrenia. Aim., This paper is a report of a study conducted to describe the prevalence of antipsychotic medication side effects in individuals with schizophrenia, and to assess if a relationship existed between side effects and medication-taking. Background., Non-adherence to antipsychotics is common in people with schizophrenia. There is a direct relationship between non-adherence and relapse, but it is unclear if an association exists between side effects and non-adherence. Method., The Liverpool University Neuroleptic Side-effect Rating Scale was used with a convenience sample of 81 mental health service users with schizophrenia. Participants were recruited from one urban and one rural area in Australia in 2004. Data were analysed using Statistical Package for Social Science and nonparametric statistical methods based on the nature of data. Findings., Around 20% of participants had missed taking their medication at least once in the week before data collection. About half experienced one or more side effects, but the level of accumulated side effects was not associated with medication omission. Older participants were more likely to experience anticholinergic and allergic side effects than their younger counterparts. Younger women were more likely to experience hormone-related side effects than older women. Overall, medication omission was not statistically significantly correlated with any of the seven Liverpool University Neuroleptic Side-effect Rating Scale subscales. Conclusion., Greater attention needs to be paid to age- and gender-specific side effects and to monitoring side effects in people prescribed atypical medication antipsychotics. Service users, case managers and prescribers may need additional training to assist them to identify side effects and to take steps to ameliorate or at least minimize their effects. [source] An examination of the intentional and unintentional aspects of medication non-adherence in patients diagnosed with hypertensionJOURNAL OF CLINICAL NURSING, Issue 4 2007Elaine Lehane MSc Aims., The primary aim of this study was to describe the unintentional and intentional aspects of non-adherence in patients diagnosed with hypertension. A secondary aim was to examine the relationships between medication adherence and purposeful actions (intentional non-adherence), patterned behaviours (unintentional non-adherence) and demographic questionnaire variables. Background., Non-adherence to medications continues to be a significant health-care issue, the extent and consequences of which have been well documented. Despite considerable research over the past five decades, little progress has been made in solving this healthcare problem. Recent literature indicates that this lack of progress can be attributed to the fact that past research has concentrated solely upon either the unintentional or the intentional aspects of non-adherence, instead of addressing both facets simultaneously. Methods., A quantitative, descriptive, correlation research design was employed using Johnson's (2002) Medication Adherence Model as a theoretical framework. A convenience sample of 73 participants with hypertension, attending the outpatients' clinics of two university hospitals was recruited. Data were collected by means of a researcher administered questionnaire and analysed using the Statistical Package for Social Sciences. Results., High levels of medication adherence with a mean adherence score of 4·75 (maximum 5) were reported. Low and medium levels of purposeful actions and medium and high levels of patterned behaviours towards medication taking were found. Correlational analyses did not demonstrate statistically significant associations. Conclusions., Both the intentional and unintentional dimensions of medication-taking are simultaneously considered by patients to varying levels when adhering to therapeutic regimens. This is an important research area for nurses as it facilitates an increased understanding of non-adherence and, in so doing, aids the uncovering of more effective interventions aimed at sustaining lifelong pharmacotherapy. Relevance to clinical practice., By acknowledging a broader approach to patient medication-taking, nurses will be able more effectively to assess and intervene in non-adherent behaviours and actions. [source] Snacking patterns influence energy and nutrient intakes but not body mass indexJOURNAL OF HUMAN NUTRITION & DIETETICS, Issue 1 2003J. S. Hampl Abstract Objective To study dietary intake and body mass index (BMI) patterns among US adults, stratified by snacking patterns. Design The 1994,1996 Continuing Survey of Food Intakes by Individuals (CSFII) provided the study sample. Snacking episodes were defined as a ,food and/or beverage break', and subjects were classified as morning, afternoon, evening, multiple or never snackers. Subjects/setting Our study included data from 1756 men and 1511 women who provided two nonconsecutive, multiple-pass 24-h dietary recalls. Statistical analyses Mean values of each subject's two 24-h recalls were used for analyses, and data were analysed using the Statistical Package for the Social Sciences (SPSS) for Windows and SUDAAN. Results Compared with women, men were more likely to be evening, multiple or never snackers. Male multiple snackers had significantly higher energy intakes than did afternoon and never snackers, whereas female multiple snackers had higher energy intakes than did morning, evening and never snackers. At the same time, male and female multiple snackers had more prudent energy-adjusted intakes of protein, cholesterol, calcium and sodium. Coffee, cola, milk, ice cream and fruits were among the most frequently consumed snacks by men and women. The BMI did not differ significantly across snacker categories. Conclusions These data indicate that snacking patterns have some effects on energy and nutrient intakes but not on BMI. Snack food choices remain a concern, especially beverages, including those that are sweetened. Vegetables and fruits as snacks should be encouraged. [source] Assessing the dietetic needs of different patient groups receiving enteral tube feeding in primary careJOURNAL OF HUMAN NUTRITION & DIETETICS, Issue 3 2002S. M. Madigan Abstract Aim To examine the nature of all contacts between adult tube-fed patients and the dietetic service and to refine the current dietetic protocols to reflect the findings of the study with a view to improving patient care. Methods All adult patients referred to the Community Nutrition and Dietetic Service within a 6-month period were included in the study. Using a proforma developed from a retrospective case-note analysis, data were collected on the complications that prompted more frequent contacts than the department protocol. Data were analysed using the Statistical Package for the Social Sciences. Results The most common indication for home enteral feeding in this group of adult patients was a swallowing disorder resulting from a cerebrovascular accident (59.5%) followed by cancer (21.5%). There was a trend for cancer patients to need more intervention compared with those patients with other medical conditions. A significant difference was observed in the total contacts and telephone calls given to those patients in there own homes (P=0.019) and there was a trend towards more domicilary visits with this group. Conclusions The department protocols have been revised to include a planned review within 2,6 weeks of initial dietetic assessment in the community for those patients who were identified to have the greatest need. More intensive dietetic monitoring has clear implications for dietetic services in the community. [source] A study of the prevalence and distribution of dentine sensitivity in a population of 17,58-year-old serving personnel on an RAF base in the MidlandsJOURNAL OF ORAL REHABILITATION, Issue 1 2002D. R. Clayton Previous studies have reported on dentine sensitivity (DS) prevalence in hospital and general practice populations. Results from these studies indicate that perception and prevalence of DS vary depending on the population. The study aimed to determine any major differences in the perception and prevalence of DS in subjects in a military training establishment. Questionnaires from 228 subjects [188 completed by males, 39 completed by females, with one person not indicating their gender of mean age 24·0 years (s.d. 7·16)] were collected and analysed using the Statistical Package for the Social Sciences (SPSS). Fifty percent of the subjects (n=114) claimed to have DS. Yet approximately 30% of the subjects (29·8%, n=68) perceived the condition as a slight problem and approximately 40% of the subjects (40·8%, n=93) claimed it was an occasional problem and approximately 50% (49·1%, n=112) did not seek treatment. Seventeen subjects (7·5%) used a desensitizing paste during periods of discomfort. No clear pattern emerged with regard to seasonal variation in DS although 5·7% (n=13) subjects considered DS to be more of a problem in winter. Only 7·9% (n=18) reported any previous periodontal surgery, consistent with previous studies (12·6 and 15·5%). Of those who received regular scaling (27·2%, n=62), only 23 (10·1%) reported any discomfort following treatment, which did not last ,5 days. The results indicate that self-reporting of DS was similar to previous reports, although it is of fundamental importance that such studies should be supplemented with a thorough clinical examination to determine more reliable prevalence data. [source] Comparison of dentine hypersensitivity in selected occidental and oriental populationsJOURNAL OF ORAL REHABILITATION, Issue 1 2001D. G. Gillam Epidemiological data on dentine hypersensitivity (DH) prevalence are limited. Few studies have compared prevalence between populations. The aim of this investigation, therefore, was to compare the perception and prevalence of DH in two distinct non-periodontal practice populations, one U.K. and one Korean. Completed questionnaires from 557 patients (230 males and 327 females, comprising 115 males and 162 females, mean age 41·7 years (s.d.=14·36), U.K. and 115 males and 165 females, mean age 29·7 years (s.d.=11·86), Korean) were collected. Analysis was by frequency distribution and cross-tabulation (Statistical Package for the Social Sciences (SPSS)). DH prevalence was similar and at levels comparable with those reported previously. Prevalence was higher in the third and fourth decades in both populations. Although there were no differences between U.K. or Korean males and U.K. or Korean females, there was a significant difference between gender reporting of DH, with more females complaining of DH than males (standard normal deviation (SND)=4·3, 95% confidence interval (CI)=0·1134,0·2736). DH appeared to be regarded by patients as not severe in most cases, so treatment was not generally sought. Of those who claimed to have sought treatment, a significant number had received restorative treatment. Of those patients, only 23·3% of U.K. and ,2% of Korean patients claimed to have used a desensitizing dentifrice. Pain from DH was reported as low grade (slight, occasional) occurring over 5 years in both populations. Cold appeared to be the most reported stimulus in the two populations. Less periodontal surgery had been undertaken in these two populations (12·6% U.K. and 7·1% Korean) compared with those referred to a teaching hospital periodontal department (34·5%). This compared favourably with previous findings in the general dental population (15·5%). Discomfort following hygiene therapy did not appear to last ,7 days in either population. The results indicated that there were no significant differences between U.K.- and Korean-based populations in their perception of DH, with the exception that more females complained of sensitivity than males in both groups. Overall, DH was not considered a major dental problem by most patients in either of the populations. [source] Multidimensional assessment of female tracheoesophageal prosthetic speechCLINICAL OTOLARYNGOLOGY, Issue 6 2006R. Kazi Objective:, The objective of this study was to undertake a multidimensional assessment of female tracheoesophageal prosthetic speech. Study Design:, A cross-sectional cohort study. Setting:, Head and Neck Unit in a tertiary oncology referral centre. Patients:, Ten female and 10 male total laryngectomy patients with no signs of recurrence and using voice prosthesis were compared to 10 normal female speakers. Intervention(s):, Electroglottographic and acoustic analysis of voice parameters for both sustained vowel /i/ and connected speech, perceptual evaluation using GRBAS (with 2 experienced raters) and questionnaire assessment using the University of Washington Quality of Life and the Voice Handicap Index. Statistical analysis was done using the Statistical Package for Social Sciences, (v. 14, SPSS Inc., Chicago III). Results:, Median age of the female larygectomy patiemts was 65 years (range: 41-81), that of male laryngectomees was 66.5 years (range: 40-79) and that of the normal female subjects was 47.5 years (range: 35-72). All electroglottographic, acoustic parameters and GRBAS ratings of the female laryngectomy patients were significantly worse as compared with the normal female subjects. The median fundamental frequency (111.8 Hz) was comparable to male tracheoesophageal speakers (115.8 Hz). Mean composite University of Washington Quality of Life score and overall Voice Handicap Index score was 79.3(12.5) and 47.5(27.6) for the female laryngectomy patients and for the males was 81.2 (9.6) and 39.4(18.7). Conclusions:, Gender frequency differences as seen in normal subjects are lost following a laryngectomy operation as evidenced by electroglottographic and perceptual data. Although the quality of life scores are comparable to the male tracheoesophageal speakers, they exhibit a greater voice handicap as compared to their male counterparts. [source] An investigation of root-fractured permanent incisor teeth in childrenDENTAL TRAUMATOLOGY, Issue 1 2003Laura Feely Abstract ,,,The aim of this retrospective study was to determine the type of healing which occurred in root-fractured permanent incisor teeth in children. The objectives were to determine whether gender, age, stage of root development or location of the fracture affected the healing type. The method involved careful scrutiny of clinical records and radiographs of children who attended a unit of paediatric dentistry in a dental hospital. Relevant information was entered onto a data collection sheet. The results were tabulated and analysed by the ,2 -tests using the SPSS statistical package. The results are based on 34 root-fractured teeth in 33 children aged 8,15 years. Root development was incomplete in 27 of the root-fractured teeth and complete in seven teeth. A good healing outcome was seen in 27 (79.4%) of the teeth and poor healing in 7 (20.6%). The only factor which was found to be statistically significantly related to healing was the stage of root development. It can be concluded that root-fractured teeth with immature roots have a better chance of showing good healing than teeth with mature roots. [source] Towards an integrated computational tool for spatial analysis in macroecology and biogeographyGLOBAL ECOLOGY, Issue 4 2006Thiago Fernando L. V. B. Rangel ABSTRACT Because most macroecological and biodiversity data are spatially autocorrelated, special tools for describing spatial structures and dealing with hypothesis testing are usually required. Unfortunately, most of these methods have not been available in a single statistical package. Consequently, using these tools is still a challenge for most ecologists and biogeographers. In this paper, we present sam (Spatial Analysis in Macroecology), a new, easy-to-use, freeware package for spatial analysis in macroecology and biogeography. Through an intuitive, fully graphical interface, this package allows the user to describe spatial patterns in variables and provides an explicit spatial framework for standard techniques of regression and correlation. Moran's I autocorrelation coefficient can be calculated based on a range of matrices describing spatial relationships, for original variables as well as for residuals of regression models, which can also include filtering components (obtained by standard trend surface analysis or by principal coordinates of neighbour matrices). sam also offers tools for correcting the number of degrees of freedom when calculating the significance of correlation coefficients. Explicit spatial modelling using several forms of autoregression and generalized least-squares models are also available. We believe this new tool will provide researchers with the basic statistical tools to resolve autocorrelation problems and, simultaneously, to explore spatial components in macroecological and biogeographical data. Although the program was designed primarily for the applications in macroecology and biogeography, most of sam's statistical tools will be useful for all kinds of surface pattern spatial analysis. The program is freely available at http://www.ecoevol.ufg.br/sam (permanent URL at http://purl.oclc.org/sam/). [source] Determination of biochemical properties of foam-mat dried mango powderINTERNATIONAL JOURNAL OF FOOD SCIENCE & TECHNOLOGY, Issue 8 2010Dattatreya M. Kadam Summary Investigations were carried out to see the impact of drying air temperature (65, 75 and 85 °C) and milk as foaming agent in different concentration levels (0%, 10%, 15%, 20% and 25%) on the chemical properties of foam-mat dried mango juice powder. Chemical properties such as total sugars, ascorbic acid, total carotenes, minerals, total acid, pH, total soluble solids (TSS) and microbial load (fungal and bacterial) of foam-mat dried mango powder were determined. Data were analysed as per two-way anova, Duncan's multiple range test and l.s.d. of AgRes Software statistical package. Almost all chemical properties show decreasing trend with increase in drying air temperature. Microbial load was not detected in foam-mat dried mango powder. It was found that addition of 10% milk as foaming agent and drying at 65 °C temperature gave better results. [source] No correlation of five gene polymorphisms with periodontal conditions in a Greek populationJOURNAL OF CLINICAL PERIODONTOLOGY, Issue 11 2006D. Sakellari Abstract Background: Various studies have examined possible correlations between a number of cytokine gene polymorphisms and periodontal disease in populations of different origins. The present study sought the correlation between four single-nucleotide polymorphisms (IL1A+3954, IL1B+4845, TNFA,308, COL1A1 Sp1), a variable number of tandem repeats polymorphism (IL1RN intron 2) and periodontal conditions in subjects of Greek origin. Methods: One hundred and ninety-two healthy subjects, stratified as non-periodontitis and periodontitis (chronic and aggressive) cases, participated in the present study. Genotyping was performed by polymerase chain reaction-based techniques using the primers and conditions described in the literature. The frequencies of genotypes between study groups were compared using Genepop v3.3 genetic software and Instat statistical package. Results: No differences were observed among the groups concerning the distributions of genotypes under investigation. Conclusions: Carriage rates of the polymorphisms under investigation in systemically healthy subjects of Greek origin are well within the range reported for Caucasians but these polymorphisms cannot discriminate between non-periodontitis and periodontitis (chronic or aggressive) cases. [source] Association between level of education and oral health status in 35-, 50-, 65- and 75-year-oldsJOURNAL OF CLINICAL PERIODONTOLOGY, Issue 8 2003J. Paulander Abstract Aim: The aim of the present study was to evaluate the association between educational level and dental disease, treatment needs and oral hygiene habits. Material and methods: Randomized samples of 35-, 50-, 65- and 75-year-olds, classified according to the educational level: [low (LE): elementary school or higher (HE)], were identified. In 1091 subjects, a number of characteristics such as (i) number of teeth, (ii) periodontal attachment levels (PAL), (iii) caries and (iv) occlusal function were recorded. Educational level, oral hygiene and dietary habits were self-reported. Non-parametric variables were analyzed by ,2, Mann,Whitney U,Wilcoxon's rank sum tests, and parametric variables by Student's t -test (level of significance 95%). A two-way anova was performed on decayed, missing and filled surfaces to investigate the interaction between age and educational level. All statistical procedures were performed in the SPSS© statistical package. Results: The number of remaining teeth was similar for LE and HE in the 35-year olds (25.8 versus 26.6), but in the older age groups LE had significantly a larger number of missing teeth. The LE groups (except in 65-year olds) exhibited significantly more PAL loss. LE had significantly fewer healthy gingival units in all but the 75-year age group. In all age groups, LE had fewer intact tooth surfaces and a significantly poorer occlusal function. The frequency of tooth cleaning measures and dietary habits did not differ between LE and HE. Conclusion: Educational level was shown to influence the oral conditions and should be considered in assessing risk, and in planning appropriate preventive measures. Zusammenfassung Ziel: Das Ziel der vorliegenden Studie war die Evaluation der Verbindung zwischen Bildungsniveau und Erkrankungen der Zähne, Behandlungsnotwendigkeit und oralen Hygienegewohnheiten. Material und Methoden: Randomisierte Gruppen von 35-, 50-, 65- und 75-Jährigen, die entsprechend ihres Bildungsniveau: niedriges Niveau (LE): Grundschule oder höheres Niveau (HE) klassifiziert wurden, wurden gebildet. Bei 1091 Personen wurden eine Anzahl von Charakteristika aufgezeichnet: (i) Anzahl der Zähne, (ii) parodontales Stützgewebeniveau (PAL), (iii) Karies, (iv) okklusale Funktion. Bildungsniveau, orale Hygiene und Eßgewohnheiten wurden selbst erfasst. Parameterfreie Variable wurden mit dem Chi-Quadrat test, dem Mann,Whitney U,Wilcoxon Rangsummentest und die parametergebundenen Variablen mit dem Student t -test (Signifikanz-Niveau 95 %) analysiert. Die Zwei-Wege ANOVA wurde auf dem DMF-s durchgeführt, um die Beziehung zwischen Alter und Bildungsniveau zu untersuchen. Alle statistischen Berechnungen wurden mit dem SPSS Statistik Programm vorgenommen. Ergebnisse: Die Anzahl der verbliebenen Zähne war zwischen LE und HE ähnlich bei den 35-Jährigen (25.8 vs. 26.6), aber in den älteren LE-Gruppen waren signifikant höhere Zahlen für fehlende Zähne. Die LE-Gruppen (ohne die 65-Jährigen) zeigten signifikant größeren PAL Verlust. LE hatten signifikant weniger gingivale Gesundheit bei den 75-Jährigen. In allen Altersgruppen hatten die LE weniger intakte Zahnoberflächen und signifikant geringere okklusale Funktion. Die Häufigkeit der Zahnreinigung und die Eßgewohnheiten unterschieden sich zwischen LE und HE nicht. Schlussfolgerung: Das Bildungsniveau hat einen Einfluss auf die oralen Bedingungen und sollte bei der Erfassung des Risikos und bei der Planung geeigneter Präventionsmaßnahmen beachtet werden. Résumé But: Le but de cette étude était d'évaluer l'association entre niveau d'éducation et maladie dentaire, besoins de traitement et habitudes d'hygiène orale. Matériel et méthodes: Des échantillons randomisés de sujets âgés de 35-, 50-, 65- et 75 ans, classés selon leur niveau d'éducation: [Bas (LE): école élémentaire, ou élevé (HE)] furent identifiés. Chez 1091 sujets, on a enregistré les caractéristiques suivantes: (i) nombre de dents, (ii) niveau d'attache parodontal (PAL), (iii) caries et (iv) fonction occlusale. Le niveau d'éducation, l'hygiène orale, et les habitudes alimentaires étaient rapportés par les patients eux-même. Les variables non paramétriques furent analysées par les tests chi carré, Mann,Whitney U,Wilcoxon rank sum, et les variables paramétriques par le test t de Student (niveau de signification 95%). 2-way ANOVA fut réalisé sur le DMFS pour rechercher l'interaction entre l'âge et le niveau d'éducation. Toutes les opérations statistiques furent menées par utilisation de SPSS©. Résultats: le nombre de dents restantesétait semblable pour LE et HE chez les sujets de 35 ans (25.8 vs. 26.6), mais dans les groupes plus âgés, LE présentait un nombre significativement plus important de dents absentes. Le groupe LE (sauf chez les patients de 65 ans) présentait plus de perte de PAL. LE présentait moins d'unités gingivales saines sauf dans le groupe de patients âgés de 75 ans. Dans tous les groupes d'âge, LE avait moins de surfaces dentaires intactes et une fonction occlusale significativement plus faible. La fréquence des mesures de nettoyage dentaire et les habitudes alimentaires n'étaient pas différentes entre les groupes LE et HE. Conclusion: Il est montré que le niveau d'éducation influence les conditions orales et cela doit être pris en considération lors de la mise en évidence du risque et dans la planification de mesures de prévention appropriées. [source] An adaptive empirical Bayesian thresholding procedure for analysing microarray experiments with replicationJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES C (APPLIED STATISTICS), Issue 3 2007Rebecca E. Walls Summary., A typical microarray experiment attempts to ascertain which genes display differential expression in different samples. We model the data by using a two-component mixture model and develop an empirical Bayesian thresholding procedure, which was originally introduced for thresholding wavelet coefficients, as an alternative to the existing methods for determining differential expression across thousands of genes. The method is built on sound theoretical properties and has easy computer implementation in the R statistical package. Furthermore, we consider improvements to the standard empirical Bayesian procedure when replication is present, to increase the robustness and reliability of the method. We provide an introduction to microarrays for those who are unfamilar with the field and the proposed procedure is demonstrated with applications to two-channel complementary DNA microarray experiments. [source] European Mathematical Genetics Meeting, Heidelberg, Germany, 12th,13th April 2007ANNALS OF HUMAN GENETICS, Issue 4 2007Article first published online: 28 MAY 200 Saurabh Ghosh 11 Indian Statistical Institute, Kolkata, India High correlations between two quantitative traits may be either due to common genetic factors or common environmental factors or a combination of both. In this study, we develop statistical methods to extract the contribution of a common QTL to the total correlation between the components of a bivariate phenotype. Using data on bivariate phenotypes and marker genotypes for sib-pairs, we propose a test for linkage between a common QTL and a marker locus based on the conditional cross-sib trait correlations (trait 1 of sib 1 , trait 2 of sib 2 and conversely) given the identity-by-descent sharing at the marker locus. The null hypothesis cannot be rejected unless there exists a common QTL. We use Monte-Carlo simulations to evaluate the performance of the proposed test under different trait parameters and quantitative trait distributions. An application of the method is illustrated using data on two alcohol-related phenotypes from the Collaborative Study On The Genetics Of Alcoholism project. Rémi Kazma 1 , Catherine Bonaïti-Pellié 1 , Emmanuelle Génin 12 INSERM UMR-S535 and Université Paris Sud, Villejuif, 94817, France Keywords: Gene-environment interaction, sibling recurrence risk, exposure correlation Gene-environment interactions may play important roles in complex disease susceptibility but their detection is often difficult. Here we show how gene-environment interactions can be detected by investigating the degree of familial aggregation according to the exposure of the probands. In case of gene-environment interaction, the distribution of genotypes of affected individuals, and consequently the risk in relatives, depends on their exposure. We developed a test comparing the risks in sibs according to the proband exposure. To evaluate the properties of this new test, we derived the formulas for calculating the expected risks in sibs according to the exposure of probands for various values of exposure frequency, relative risk due to exposure alone, frequencies of latent susceptibility genotypes, genetic relative risks and interaction coefficients. We find that the ratio of risks when the proband is exposed and not exposed is a good indicator of the interaction effect. We evaluate the power of the test for various sample sizes of affected individuals. We conclude that this test is valuable for diseases with moderate familial aggregation, only when the role of the exposure has been clearly evidenced. Since a correlation for exposure among sibs might lead to a difference in risks among sibs in the different proband exposure strata, we also add an exposure correlation coefficient in the model. Interestingly, we find that when this correlation is correctly accounted for, the power of the test is not decreased and might even be significantly increased. Andrea Callegaro 1 , Hans J.C. Van Houwelingen 1 , Jeanine Houwing-Duistermaat 13 Dept. of Medical Statistics and Bioinformatics, Leiden University Medical Center, The Netherlands Keywords: Survival analysis, age at onset, score test, linkage analysis Non parametric linkage (NPL) analysis compares the identical by descent (IBD) sharing in sibling pairs to the expected IBD sharing under the hypothesis of no linkage. Often information is available on the marginal cumulative hazards (for example breast cancer incidence curves). Our aim is to extend the NPL methods by taking into account the age at onset of selected sibling pairs using these known marginal hazards. Li and Zhong (2002) proposed a (retrospective) likelihood ratio test based on an additive frailty model for genetic linkage analysis. From their model we derive a score statistic for selected samples which turns out to be a weighed NPL method. The weights depend on the marginal cumulative hazards and on the frailty parameter. A second approach is based on a simple gamma shared frailty model. Here, we simply test whether the score function of the frailty parameter depends on the excess IBD. We compare the performance of these methods using simulated data. Céline Bellenguez 1 , Carole Ober 2 , Catherine Bourgain 14 INSERM U535 and University Paris Sud, Villejuif, France 5 Department of Human Genetics, The University of Chicago, USA Keywords: Linkage analysis, linkage disequilibrium, high density SNP data Compared with microsatellite markers, high density SNP maps should be more informative for linkage analyses. However, because they are much closer, SNPs present important linkage disequilibrium (LD), which biases classical nonparametric multipoint analyses. This problem is even stronger in population isolates where LD extends over larger regions with a more stochastic pattern. We investigate the issue of linkage analysis with a 500K SNP map in a large and inbred 1840-member Hutterite pedigree, phenotyped for asthma. Using an efficient pedigree breaking strategy, we first identified linked regions with a 5cM microsatellite map, on which we focused to evaluate the SNP map. The only method that models LD in the NPL analysis is limited in both the pedigree size and the number of markers (Abecasis and Wigginton, 2005) and therefore could not be used. Instead, we studied methods that identify sets of SNPs with maximum linkage information content in our pedigree and no LD-driven bias. Both algorithms that directly remove pairs of SNPs in high LD and clustering methods were evaluated. Null simulations were performed to control that Zlr calculated with the SNP sets were not falsely inflated. Preliminary results suggest that although LD is strong in such populations, linkage information content slightly better than that of microsatellite maps can be extracted from dense SNP maps, provided that a careful marker selection is conducted. In particular, we show that the specific LD pattern requires considering LD between a wide range of marker pairs rather than only in predefined blocks. Peter Van Loo 1,2,3 , Stein Aerts 1,2 , Diether Lambrechts 4,5 , Bernard Thienpont 2 , Sunit Maity 4,5 , Bert Coessens 3 , Frederik De Smet 4,5 , Leon-Charles Tranchevent 3 , Bart De Moor 2 , Koen Devriendt 3 , Peter Marynen 1,2 , Bassem Hassan 1,2 , Peter Carmeliet 4,5 , Yves Moreau 36 Department of Molecular and Developmental Genetics, VIB, Belgium 7 Department of Human Genetics, University of Leuven, Belgium 8 Bioinformatics group, Department of Electrical Engineering, University of Leuven, Belgium 9 Department of Transgene Technology and Gene Therapy, VIB, Belgium 10 Center for Transgene Technology and Gene Therapy, University of Leuven, Belgium Keywords: Bioinformatics, gene prioritization, data fusion The identification of genes involved in health and disease remains a formidable challenge. Here, we describe a novel bioinformatics method to prioritize candidate genes underlying pathways or diseases, based on their similarity to genes known to be involved in these processes. It is freely accessible as an interactive software tool, ENDEAVOUR, at http://www.esat.kuleuven.be/endeavour. Unlike previous methods, ENDEAVOUR generates distinct prioritizations from multiple heterogeneous data sources, which are then integrated, or fused, into one global ranking using order statistics. ENDEAVOUR prioritizes candidate genes in a three-step process. First, information about a disease or pathway is gathered from a set of known "training" genes by consulting multiple data sources. Next, the candidate genes are ranked based on similarity with the training properties obtained in the first step, resulting in one prioritized list for each data source. Finally, ENDEAVOUR fuses each of these rankings into a single global ranking, providing an overall prioritization of the candidate genes. Validation of ENDEAVOUR revealed it was able to efficiently prioritize 627 genes in disease data sets and 76 genes in biological pathway sets, identify candidates of 16 mono- or polygenic diseases, and discover regulatory genes of myeloid differentiation. Furthermore, the approach identified YPEL1 as a novel gene involved in craniofacial development from a 2-Mb chromosomal region, deleted in some patients with DiGeorge-like birth defects. Finally, we are currently evaluating a pipeline combining array-CGH, ENDEAVOUR and in vivo validation in zebrafish to identify novel genes involved in congenital heart defects. Mark Broom 1 , Graeme Ruxton 2 , Rebecca Kilner 311 Mathematics Dept., University of Sussex, UK 12 Division of Environmental and Evolutionary Biology, University of Glasgow, UK 13 Department of Zoology, University of Cambridge, UK Keywords: Evolutionarily stable strategy, parasitism, asymmetric game Brood parasites chicks vary in the harm that they do to their companions in the nest. In this presentation we use game-theoretic methods to model this variation. Our model considers hosts which potentially abandon single nestlings and instead choose to re-allocate their reproductive effort to future breeding, irrespective of whether the abandoned chick is the host's young or a brood parasite's. The parasite chick must decide whether or not to kill host young by balancing the benefits from reduced competition in the nest against the risk of desertion by host parents. The model predicts that three different types of evolutionarily stable strategies can exist. (1) Hosts routinely rear depleted broods, the brood parasite always kills host young and the host never then abandons the nest. (2) When adult survival after deserting single offspring is very high, hosts always abandon broods of a single nestling and the parasite never kills host offspring, effectively holding them as hostages to prevent nest desertion. (3) Intermediate strategies, in which parasites sometimes kill their nest-mates and host parents sometimes desert nests that contain only a single chick, can also be evolutionarily stable. We provide quantitative descriptions of how the values given to ecological and behavioral parameters of the host-parasite system influence the likelihood of each strategy and compare our results with real host-brood parasite associations in nature. Martin Harrison 114 Mathematics Dept, University of Sussex, UK Keywords: Brood parasitism, games, host, parasite The interaction between hosts and parasites in bird populations has been studied extensively. Game theoretical methods have been used to model this interaction previously, but this has not been studied extensively taking into account the sequential nature of this game. We consider a model allowing the host and parasite to make a number of decisions, which depend on a number of natural factors. The host lays an egg, a parasite bird will arrive at the nest with a certain probability and then chooses to destroy a number of the host eggs and lay one of it's own. With some destruction occurring, either natural or through the actions of the parasite, the host chooses to continue, eject an egg (hoping to eject the parasite) or abandon the nest. Once the eggs have hatched the game then falls to the parasite chick versus the host. The chick chooses to destroy or eject a number of eggs. The final decision is made by the host, choosing whether to raise or abandon the chicks that are in the nest. We consider various natural parameters and probabilities which influence these decisions. We then use this model to look at real-world situations of the interactions of the Reed Warbler and two different parasites, the Common Cuckoo and the Brown-Headed Cowbird. These two parasites have different methods in the way that they parasitize the nests of their hosts. The hosts in turn have a different reaction to these parasites. Arne Jochens 1 , Amke Caliebe 2 , Uwe Roesler 1 , Michael Krawczak 215 Mathematical Seminar, University of Kiel, Germany 16 Institute of Medical Informatics and Statistics, University of Kiel, Germany Keywords: Stepwise mutation model, microsatellite, recursion equation, temporal behaviour We consider the stepwise mutation model which occurs, e.g., in microsatellite loci. Let X(t,i) denote the allelic state of individual i at time t. We compute expectation, variance and covariance of X(t,i), i=1,,,N, and provide a recursion equation for P(X(t,i)=z). Because the variance of X(t,i) goes to infinity as t grows, for the description of the temporal behaviour, we regard the scaled process X(t,i)-X(t,1). The results furnish a better understanding of the behaviour of the stepwise mutation model and may in future be used to derive tests for neutrality under this model. Paul O'Reilly 1 , Ewan Birney 2 , David Balding 117 Statistical Genetics, Department of Epidemiology and Public Health, Imperial, College London, UK 18 European Bioinformatics Institute, EMBL, Cambridge, UK Keywords: Positive selection, Recombination rate, LD, Genome-wide, Natural Selection In recent years efforts to develop population genetics methods that estimate rates of recombination and levels of natural selection in the human genome have intensified. However, since the two processes have an intimately related impact on genetic variation their inference is vulnerable to confounding. Genomic regions subject to recent selection are likely to have a relatively recent common ancestor and consequently less opportunity for historical recombinations that are detectable in contemporary populations. Here we show that selection can reduce the population-based recombination rate estimate substantially. In genome-wide studies for detecting selection we observe a tendency to highlight loci that are subject to low levels of recombination. We find that the outlier approach commonly adopted in such studies may have low power unless variable recombination is accounted for. We introduce a new genome-wide method for detecting selection that exploits the sensitivity to recent selection of methods for estimating recombination rates, while accounting for variable recombination using pedigree data. Through simulations we demonstrate the high power of the Ped/Pop approach to discriminate between neutral and adaptive evolution, particularly in the context of choosing outliers from a genome-wide distribution. Although methods have been developed showing good power to detect selection ,in action', the corresponding window of opportunity is small. In contrast, the power of the Ped/Pop method is maintained for many generations after the fixation of an advantageous variant Sarah Griffiths 1 , Frank Dudbridge 120 MRC Biostatistics Unit, Cambridge, UK Keywords: Genetic association, multimarker tag, haplotype, likelihood analysis In association studies it is generally too expensive to genotype all variants in all subjects. We can exploit linkage disequilibrium between SNPs to select a subset that captures the variation in a training data set obtained either through direct resequencing or a public resource such as the HapMap. These ,tag SNPs' are then genotyped in the whole sample. Multimarker tagging is a more aggressive adaptation of pairwise tagging that allows for combinations of two or more tag SNPs to predict an untyped SNP. Here we describe a new method for directly testing the association of an untyped SNP using a multimarker tag. Previously, other investigators have suggested testing a specific tag haplotype, or performing a weighted analysis using weights derived from the training data. However these approaches do not properly account for the imperfect correlation between the tag haplotype and the untyped SNP. Here we describe a straightforward approach to testing untyped SNPs using a missing-data likelihood analysis, including the tag markers as nuisance parameters. The training data is stacked on top of the main body of genotype data so there is information on how the tag markers predict the genotype of the untyped SNP. The uncertainty in this prediction is automatically taken into account in the likelihood analysis. This approach yields more power and also a more accurate prediction of the odds ratio of the untyped SNP. Anke Schulz 1 , Christine Fischer 2 , Jenny Chang-Claude 1 , Lars Beckmann 121 Division of Cancer Epidemiology, German Cancer Research Center (DKFZ) Heidelberg, Germany 22 Institute of Human Genetics, University of Heidelberg, Germany Keywords: Haplotype, haplotype sharing, entropy, Mantel statistics, marker selection We previously introduced a new method to map genes involved in complex diseases, using haplotype sharing-based Mantel statistics to correlate genetic and phenotypic similarity. Although the Mantel statistic is powerful in narrowing down candidate regions, the precise localization of a gene is hampered in genomic regions where linkage disequilibrium is so high that neighboring markers are found to be significant at similar magnitude and we are not able to discriminate between them. Here, we present a new approach to localize susceptibility genes by combining haplotype sharing-based Mantel statistics with an iterative entropy-based marker selection algorithm. For each marker at which the Mantel statistic is evaluated, the algorithm selects a subset of surrounding markers. The subset is chosen to maximize multilocus linkage disequilibrium, which is measured by the normalized entropy difference introduced by Nothnagel et al. (2002). We evaluated the algorithm with respect to type I error and power. Its ability to localize the disease variant was compared to the localization (i) without marker selection and (ii) considering haplotype block structure. Case-control samples were simulated from a set of 18 haplotypes, consisting of 15 SNPs in two haplotype blocks. The new algorithm gave correct type I error and yielded similar power to detect the disease locus compared to the alternative approaches. The neighboring markers were clearly less often significant than the causal locus, and also less often significant compared to the alternative approaches. Thus the new algorithm improved the precision of the localization of susceptibility genes. Mark M. Iles 123 Section of Epidemiology and Biostatistics, LIMM, University of Leeds, UK Keywords: tSNP, tagging, association, HapMap Tagging SNPs (tSNPs) are commonly used to capture genetic diversity cost-effectively. However, it is important that the efficacy of tSNPs is correctly estimated, otherwise coverage may be insufficient. If the pilot sample from which tSNPs are chosen is too small or the initial marker map too sparse, tSNP efficacy may be overestimated. An existing estimation method based on bootstrapping goes some way to correct for insufficient sample size and overfitting, but does not completely solve the problem. We describe a novel method, based on exclusion of haplotypes, that improves on the bootstrap approach. Using simulated data, the extent of the sample size problem is investigated and the performance of the bootstrap and the novel method are compared. We incorporate an existing method adjusting for marker density by ,SNP-dropping'. We find that insufficient sample size can cause large overestimates in tSNP efficacy, even with as many as 100 individuals, and the problem worsens as the region studied increases in size. Both the bootstrap and novel method correct much of this overestimate, with our novel method consistently outperforming the bootstrap method. We conclude that a combination of insufficient sample size and overfitting may lead to overestimation of tSNP efficacy and underpowering of studies based on tSNPs. Our novel approach corrects for much of this bias and is superior to the previous method. Sample sizes larger than previously suggested may still be required for accurate estimation of tSNP efficacy. This has obvious ramifications for the selection of tSNPs from HapMap data. Claudio Verzilli 1 , Juliet Chapman 1 , Aroon Hingorani 2 , Juan Pablo-Casas 1 , Tina Shah 2 , Liam Smeeth 1 , John Whittaker 124 Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, UK 25 Division of Medicine, University College London, UK Keywords: Meta-analysis, Genetic association studies We present a Bayesian hierarchical model for the meta-analysis of candidate gene studies with a continuous outcome. Such studies often report results from association tests for different, possibly study-specific and non-overlapping markers (typically SNPs) in the same genetic region. Meta analyses of the results at each marker in isolation are seldom appropriate as they ignore the correlation that may exist between markers due to linkage disequlibrium (LD) and cannot assess the relative importance of variants at each marker. Also such marker-wise meta analyses are restricted to only those studies that have typed the marker in question, with a potential loss of power. A better strategy is one which incorporates information about the LD between markers so that any combined estimate of the effect of each variant is corrected for the effect of other variants, as in multiple regression. Here we develop a Bayesian hierarchical linear regression that models the observed genotype group means and uses pairwise LD measurements between markers as prior information to make posterior inference on adjusted effects. The approach is applied to the meta analysis of 24 studies assessing the effect of 7 variants in the C-reactive protein (CRP) gene region on plasma CRP levels, an inflammatory biomarker shown in observational studies to be positively associated with cardiovascular disease. Cathryn M. Lewis 1 , Christopher G. Mathew 1 , Theresa M. Marteau 226 Dept. of Medical and Molecular Genetics, King's College London, UK 27 Department of Psychology, King's College London, UK Keywords: Risk, genetics, CARD15, smoking, model Recently progress has been made in identifying mutations that confer susceptibility to complex diseases, with the potential to use these mutations in determining disease risk. We developed methods to estimate disease risk based on genotype relative risks (for a gene G), exposure to an environmental factor (E), and family history (with recurrence risk ,R for a relative of type R). ,R must be partitioned into the risk due to G (which is modelled independently) and the residual risk. The risk model was then applied to Crohn's disease (CD), a severe gastrointestinal disease for which smoking increases disease risk approximately 2-fold, and mutations in CARD15 confer increased risks of 2.25 (for carriers of a single mutation) and 9.3 (for carriers of two mutations). CARD15 accounts for only a small proportion of the genetic component of CD, with a gene-specific ,S, CARD15 of 1.16, from a total sibling relative risk of ,S= 27. CD risks were estimated for high-risk individuals who are siblings of a CD case, and who also smoke. The CD risk to such individuals who carry two CARD15 mutations is approximately 0.34, and for those carrying a single CARD15 mutation the risk is 0.08, compared to a population prevalence of approximately 0.001. These results imply that complex disease genes may be valuable in estimating with greater precision than has hitherto been possible disease risks in specific, easily identified subgroups of the population with a view to prevention. Yurii Aulchenko 128 Department of Epidemiology & Biostatistics, Erasmus Medical Centre Rotterdam, The Netherlands Keywords: Compression, information, bzip2, genome-wide SNP data, statistical genetics With advances in molecular technology, studies accessing millions of genetic polymorphisms in thousands of study subjects will soon become common. Such studies generate large amounts of data, whose effective storage and management is a challenge to the modern statistical genetics. Standard file compression utilities, such as Zip, Gzip and Bzip2, may be helpful to minimise the storage requirements. Less obvious is the fact that the data compression techniques may be also used in the analysis of genetic data. It is known that the efficiency of a particular compression algorithm depends on the probability structure of the data. In this work, we compared different standard and customised tools using the data from human HapMap project. Secondly, we investigate the potential uses of data compression techniques for the analysis of linkage, association and linkage disequilibrium Suzanne Leal 1 , Bingshan Li 129 Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, USA Keywords: Consanguineous pedigrees, missing genotype data Missing genotype data can increase false-positive evidence for linkage when either parametric or nonparametric analysis is carried out ignoring intermarker linkage disequilibrium (LD). Previously it was demonstrated by Huang et al (2005) that no bias occurs in this situation for affected sib-pairs with unrelated parents when either both parents are genotyped or genotype data is available for two additional unaffected siblings when parental genotypes are missing. However, this is not the case for consanguineous pedigrees, where missing genotype data for any pedigree member within a consanguinity loop can increase false-positive evidence of linkage. The false-positive evidence for linkage is further increased when cryptic consanguinity is present. The amount of false-positive evidence for linkage is highly dependent on which family members are genotyped. When parental genotype data is available, the false-positive evidence for linkage is usually not as strong as when parental genotype data is unavailable. Which family members will aid in the reduction of false-positive evidence of linkage is highly dependent on which other family members are genotyped. For a pedigree with an affected proband whose first-cousin parents have been genotyped, further reduction in the false-positive evidence of linkage can be obtained by including genotype data from additional affected siblings of the proband or genotype data from the proband's sibling-grandparents. When parental genotypes are not available, false-positive evidence for linkage can be reduced by including in the analysis genotype data from either unaffected siblings of the proband or the proband's married-in-grandparents. Najaf Amin 1 , Yurii Aulchenko 130 Department of Epidemiology & Biostatistics, Erasmus Medical Centre Rotterdam, The Netherlands Keywords: Genomic Control, pedigree structure, quantitative traits The Genomic Control (GC) method was originally developed to control for population stratification and cryptic relatedness in association studies. This method assumes that the effect of population substructure on the test statistics is essentially constant across the genome, and therefore unassociated markers can be used to estimate the effect of confounding onto the test statistic. The properties of GC method were extensively investigated for different stratification scenarios, and compared to alternative methods, such as the transmission-disequilibrium test. The potential of this method to correct not for occasional cryptic relations, but for regular pedigree structure, however, was not investigated before. In this work we investigate the potential of the GC method for pedigree-based association analysis of quantitative traits. The power and type one error of the method was compared to standard methods, such as the measured genotype (MG) approach and quantitative trait transmission-disequilibrium test. In human pedigrees, with trait heritability varying from 30 to 80%, the power of MG and GC approach was always higher than that of TDT. GC had correct type 1 error and its power was close to that of MG under moderate heritability (30%), but decreased with higher heritability. William Astle 1 , Chris Holmes 2 , David Balding 131 Department of Epidemiology and Public Health, Imperial College London, UK 32 Department of Statistics, University of Oxford, UK Keywords: Population structure, association studies, genetic epidemiology, statistical genetics In the analysis of population association studies, Genomic Control (Devlin & Roeder, 1999) (GC) adjusts the Armitage test statistic to correct the type I error for the effects of population substructure, but its power is often sub-optimal. Turbo Genomic Control (TGC) generalises GC to incorporate co-variation of relatedness and phenotype, retaining control over type I error while improving power. TGC is similar to the method of Yu et al. (2006), but we extend it to binary (case-control) in addition to quantitative phenotypes, we implement improved estimation of relatedness coefficients, and we derive an explicit statistic that generalizes the Armitage test statistic and is fast to compute. TGC also has similarities to EIGENSTRAT (Price et al., 2006) which is a new method based on principle components analysis. The problems of population structure(Clayton et al., 2005) and cryptic relatedness (Voight & Pritchard, 2005) are essentially the same: if patterns of shared ancestry differ between cases and controls, whether distant (coancestry) or recent (cryptic relatedness), false positives can arise and power can be diminished. With large numbers of widely-spaced genetic markers, coancestry can now be measured accurately for each pair of individuals via patterns of allele-sharing. Instead of modelling subpopulations, we work instead with a coancestry coefficient for each pair of individuals in the study. We explain the relationships between TGC, GC and EIGENSTRAT. We present simulation studies and real data analyses to illustrate the power advantage of TGC in a range of scenarios incorporating both substructure and cryptic relatedness. References Clayton, D. G.et al. (2005) Population structure, differential bias and genomic control in a large-scale case-control association study. Nature Genetics37(11) November 2005. Devlin, B. & Roeder, K. (1999) Genomic control for association studies. Biometics55(4) December 1999. Price, A. L.et al. (2006) Principal components analysis corrects for stratification in genome-wide association studies. Nature Genetics38(8) (August 2006). Voight, B. J. & Pritchard, J. K. (2005) Confounding from cryptic relatedness in case-control association studies. Public Library of Science Genetics1(3) September 2005. Yu, J.et al. (2006) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nature Genetics38(2) February 2006. Hervé Perdry 1 , Marie-Claude Babron 1 , Françoise Clerget-Darpoux 133 INSERM U535 and Univ. Paris Sud, UMR-S 535, Villejuif, France Keywords: Modifier genes, case-parents trios, ordered transmission disequilibrium test A modifying locus is a polymorphic locus, distinct from the disease locus, which leads to differences in the disease phenotype, either by modifying the penetrance of the disease allele, or by modifying the expression of the disease. The effect of such a locus is a clinical heterogeneity that can be reflected by the values of an appropriate covariate, such as the age of onset, or the severity of the disease. We designed the Ordered Transmission Disequilibrium Test (OTDT) to test for a relation between the clinical heterogeneity, expressed by the covariate, and marker genotypes of a candidate gene. The method applies to trio families with one affected child and his parents. Each family member is genotyped at a bi-allelic marker M of a candidate gene. To each of the families is associated a covariate value; the families are ordered on the values of this covariate. As the TDT (Spielman et al. 1993), the OTDT is based on the observation of the transmission rate T of a given allele at M. The OTDT aims to find a critical value of the covariate which separates the sample of families in two subsamples in which the transmission rates are significantly different. We investigate the power of the method by simulations under various genetic models and covariate distributions. Acknowledgments H Perdry is funded by ARSEP. Pascal Croiseau 1 , Heather Cordell 2 , Emmanuelle Génin 134 INSERM U535 and University Paris Sud, UMR-S535, Villejuif, France 35 Institute of Human Genetics, Newcastle University, UK Keywords: Association, missing data, conditionnal logistic regression Missing data is an important problem in association studies. Several methods used to test for association need that individuals be genotyped at the full set of markers. Individuals with missing data need to be excluded from the analysis. This could involve an important decrease in sample size and a loss of information. If the disease susceptibility locus (DSL) is poorly typed, it is also possible that a marker in linkage disequilibrium gives a stronger association signal than the DSL. One may then falsely conclude that the marker is more likely to be the DSL. We recently developed a Multiple Imputation method to infer missing data on case-parent trios Starting from the observed data, a few number of complete data sets are generated by Markov-Chain Monte Carlo approach. These complete datasets are analysed using standard statistical package and the results are combined as described in Little & Rubin (2002). Here we report the results of simulations performed to examine, for different patterns of missing data, how often the true DSL gives the highest association score among different loci in LD. We found that multiple imputation usually correctly detect the DSL site even if the percentage of missing data is high. This is not the case for the naïve approach that consists in discarding trios with missing data. In conclusion, Multiple imputation presents the advantage of being easy to use and flexible and is therefore a promising tool in the search for DSL involved in complex diseases. Salma Kotti 1 , Heike Bickeböller 2 , Françoise Clerget-Darpoux 136 University Paris Sud, UMR-S535, Villejuif, France 37 Department of Genetic Epidemiology, Medical School, University of Göttingen, Germany Keywords: Genotype relative risk, internal controls, Family based analyses Family based analyses using internal controls are very popular both for detecting the effect of a genetic factor and for estimating the relative disease risk on the corresponding genotypes. Two different procedures are often applied to reconstitute internal controls. The first one considers one pseudocontrol genotype formed by the parental non-transmitted alleles called also 1:1 matching of alleles, while the second corresponds to three pseudocontrols corresponding to all genotypes formed by the parental alleles except the one of the case (1:3 matching). Many studies have compared between the two procedures in terms of the power and have concluded that the difference depends on the underlying genetic model and the allele frequencies. However, the estimation of the Genotype Relative Risk (GRR) under the two procedures has not been studied. Based on the fact that on the 1:1 matching, the control group is composed of the alleles untransmitted to the affected child and on the 1:3 matching, the control group is composed amongst alleles already transmitted to the affected child, we expect a difference on the GRR estimation. In fact, we suspect that the second procedure leads to biased estimation of the GRRs. We will analytically derive the GRR estimators for the 1:1 and 1:3 matching and will present the results at the meeting. Family based analyses using internal controls are very popular both for detecting the effect of a genetic factor and for estimating the relative disease risk on the corresponding genotypes. Two different procedures are often applied to reconstitute internal controls. The first one considers one pseudocontrol genotype formed by the parental non-transmitted alleles called also 1:1 matching of alleles, while the second corresponds to three pseudocontrols corresponding to all genotypes formed by the parental alleles except the one of the case (1:3 matching). Many studies have compared between the two procedures in terms of the power and have concluded that the difference depends on the underlying genetic model and the allele frequencies. However, the estimation of the Genotype Relative Risk (GRR) under the two procedures has not been studied. Based on the fact that on the 1:1 matching, the control group is composed of the alleles untransmitted to the affected child and on the 1:3 matching, the control group is composed amongst alleles already transmitted to the affected child, we expect a difference on the GRR estimation. In fact, we suspect that the second procedure leads to biased estimation of the GRR. We will analytically derive the GRR estimator for the 1:1 and 1:3 matching and will present the results at the meeting. Luigi Palla 1 , David Siegmund 239 Department of Mathematics,Free University Amsterdam, The Netherlands 40 Department of Statistics, Stanford University, California, USA Keywords: TDT, assortative mating, inbreeding, statistical power A substantial amount of Assortative Mating (AM) is often recorded on physical and psychological, dichotomous as well as quantitative traits that are supposed to have a multifactorial genetic component. In particular AM has the effect of increasing the genetic variance, even more than inbreeding because it acts across loci beside within loci, when the trait has a multifactorial origin. Under the assumption of a polygenic model for AM dating back to Wright (1921) and refined by Crow and Felsenstein (1968,1982), the effect of assortative mating on the power to detect genetic association in the Transmission Disequilibrium Test (TDT) is explored as parameters, such as the effective number of genes and the allelic frequency vary. The power is reflected by the non centrality parameter of the TDT and is expressed as a function of the number of trios, the relative risk of the heterozygous genotype and the allele frequency (Siegmund and Yakir, 2007). The noncentrality parameter of the relevant score statistic is updated considering the effect of AM which is expressed in terms of an ,effective' inbreeding coefficient. In particular, for dichotomous traits it is apparent that the higher the number of genes involved in the trait, the lower the loss in power due to AM. Finally an attempt is made to extend this relation to the Q-TDT (Rabinowitz, 1997), which involves considering the effect of AM also on the phenotypic variance of the trait of interest, under the assumption that AM affects only its additive genetic component. References Crow, & Felsenstein, (1968). The effect of assortative mating on the genetic composition of a population. Eugen.Quart.15, 87,97. Rabinowitz,, 1997. A Transmission Disequilibrium Test for Quantitative Trait Loci. Human Heredity47, 342,350. Siegmund, & Yakir, (2007) Statistics of gene mapping, Springer. Wright, (1921). System of mating.III. Assortative mating based on somatic resemblance. Genetics6, 144,161. Jérémie Nsengimana 1 , Ben D Brown 2 , Alistair S Hall 2 , Jenny H Barrett 141 Leeds Institute of Molecular Medicine, University of Leeds, UK 42 Leeds Institute for Genetics, Health and Therapeutics, University of Leeds, UK Keywords: Inflammatory genes, haplotype, coronary artery disease Genetic Risk of Acute Coronary Events (GRACE) is an initiative to collect cases of coronary artery disease (CAD) and their unaffected siblings in the UK and to use them to map genetic variants increasing disease risk. The aim of the present study was to test the association between CAD and 51 single nucleotide polymorphisms (SNPs) and their haplotypes from 35 inflammatory genes. Genotype data were available for 1154 persons affected before age 66 (including 48% before age 50) and their 1545 unaffected siblings (891 discordant families). Each SNP was tested for association to CAD, and haplotypes within genes or gene clusters were tested using FBAT (Rabinowitz & Laird, 2000). For the most significant results, genetic effect size was estimated using conditional logistic regression (CLR) within STATA adjusting for other risk factors. Haplotypes were assigned using HAPLORE (Zhang et al., 2005), which considers all parental mating types consistent with offspring genotypes and assigns them a probability of occurence. This probability was used in CLR to weight the haplotypes. In the single SNP analysis, several SNPs showed some evidence for association, including one SNP in the interleukin-1A gene. Analysing haplotypes in the interleukin-1 gene cluster, a common 3-SNP haplotype was found to increase the risk of CAD (P = 0.009). In an additive genetic model adjusting for covariates the odds ratio (OR) for this haplotype is 1.56 (95% CI: 1.16-2.10, p = 0.004) for early-onset CAD (before age 50). This study illustrates the utility of haplotype analysis in family-based association studies to investigate candidate genes. References Rabinowitz, D. & Laird, N. M. (2000) Hum Hered50, 211,223. Zhang, K., Sun, F. & Zhao, H. (2005) Bioinformatics21, 90,103. Andrea Foulkes 1 , Recai Yucel 1 , Xiaohong Li 143 Division of Biostatistics, University of Massachusetts, USA Keywords: Haploytpe, high-dimensional, mixed modeling The explosion of molecular level information coupled with large epidemiological studies presents an exciting opportunity to uncover the genetic underpinnings of complex diseases; however, several analytical challenges remain to be addressed. Characterizing the components to complex diseases inevitably requires consideration of synergies across multiple genetic loci and environmental and demographic factors. In addition, it is critical to capture information on allelic phase, that is whether alleles within a gene are in cis (on the same chromosome) or in trans (on different chromosomes.) In associations studies of unrelated individuals, this alignment of alleles within a chromosomal copy is generally not observed. We address the potential ambiguity in allelic phase in this high dimensional data setting using mixed effects models. Both a semi-parametric and fully likelihood-based approach to estimation are considered to account for missingness in cluster identifiers. In the first case, we apply a multiple imputation procedure coupled with a first stage expectation maximization algorithm for parameter estimation. A bootstrap approach is employed to assess sensitivity to variability induced by parameter estimation. Secondly, a fully likelihood-based approach using an expectation conditional maximization algorithm is described. Notably, these models allow for characterizing high-order gene-gene interactions while providing a flexible statistical framework to account for the confounding or mediating role of person specific covariates. The proposed method is applied to data arising from a cohort of human immunodeficiency virus type-1 (HIV-1) infected individuals at risk for therapy associated dyslipidemia. Simulation studies demonstrate reasonable power and control of family-wise type 1 error rates. Vivien Marquard 1 , Lars Beckmann 1 , Jenny Chang-Claude 144 Division of Cancer Epidemiology, German Cancer Research Center (DKFZ) Heidelberg, Germany Keywords: Genotyping errors, type I error, haplotype-based association methods It has been shown in several simulation studies that genotyping errors may have a great impact on the type I error of statistical methods used in genetic association analysis of complex diseases. Our aim was to investigate type I error rates in a case-control study, when differential and non-differential genotyping errors were introduced in realistic scenarios. We simulated case-control data sets, where individual genotypes were drawn from a haplotype distribution of 18 haplotypes with 15 markers in the APM1 gene. Genotyping errors were introduced following the unrestricted and symmetric with 0 edges error models described by Heid et al. (2006). In six scenarios, errors resulted from changes of one allele to another with predefined probabilities of 1%, 2.5% or 10%, respectively. A multiple number of errors per haplotype was possible and could vary between 0 and 15, the number of markers investigated. We examined three association methods: Mantel statistics using haplotype-sharing; a haplotype-specific score test; and Armitage trend test for single markers. The type I error rates were not influenced for any of all the three methods for a genotyping error rate of less than 1%. For higher error rates and differential errors, the type I error of the Mantel statistic was only slightly and of the Armitage trend test moderately increased. The type I error rates of the score test were highly increased. The type I error rates were correct for all three methods for non-differential errors. Further investigations will be carried out with different frequencies of differential error rates and focus on power. Arne Neumann 1 , Dörthe Malzahn 1 , Martina Müller 2 , Heike Bickeböller 145 Department of Genetic Epidemiology, Medical School, University of Göttingen, Germany 46 GSF-National Research Center for Environment and Health, Neuherberg & IBE-Institute of Epidemiology, Ludwig-Maximilians University München, Germany Keywords: Interaction, longitudinal, nonparametric Longitudinal data show the time dependent course of phenotypic traits. In this contribution, we consider longitudinal cohort studies and investigate the association between two candidate genes and a dependent quantitative longitudinal phenotype. The set-up defines a factorial design which allows us to test simultaneously for the overall gene effect of the loci as well as for possible gene-gene and gene time interaction. The latter would induce genetically based time-profile differences in the longitudinal phenotype. We adopt a non-parametric statistical test to genetic epidemiological cohort studies and investigate its performance by simulation studies. The statistical test was originally developed for longitudinal clinical studies (Brunner, Munzel, Puri, 1999 J Multivariate Anal 70:286-317). It is non-parametric in the sense that no assumptions are made about the underlying distribution of the quantitative phenotype. Longitudinal observations belonging to the same individual can be arbitrarily dependent on one another for the different time points whereas trait observations of different individuals are independent. The two loci are assumed to be statistically independent. Our simulations show that the nonparametric test is comparable with ANOVA in terms of power of detecting gene-gene and gene-time interaction in an ANOVA favourable setting. Rebecca Hein 1 , Lars Beckmann 1 , Jenny Chang-Claude 147 Division of Cancer Epidemiology, German Cancer Research Center (DKFZ) Heidelberg, Germany Keywords: Indirect association studies, interaction effects, linkage disequilibrium, marker allele frequency Association studies accounting for gene-environment interactions (GxE) may be useful for detecting genetic effects and identifying important environmental effect modifiers. Current technology facilitates very dense marker spacing in genetic association studies; however, the true disease variant(s) may not be genotyped. In this situation, an association between a gene and a phenotype may still be detectable, using genetic markers associated with the true disease variant(s) (indirect association). Zondervan and Cardon [2004] showed that the odds ratios (OR) of markers which are associated with the disease variant depend highly on the linkage disequilibrium (LD) between the variant and the markers, and whether the allele frequencies match and thereby influence the sample size needed to detect genetic association. We examined the influence of LD and allele frequencies on the sample size needed to detect GxE in indirect association studies, and provide tables for sample size estimation. For discordant allele frequencies and incomplete LD, sample sizes can be unfeasibly large. The influence of both factors is stronger for disease loci with small rather than moderate to high disease allele frequencies. A decline in D' of e.g. 5% has less impact on sample size than increasing the difference in allele frequencies by the same percentage. Assuming 80% power, large interaction effects can be detected using smaller sample sizes than those needed for the detection of main effects. The detection of interaction effects involving rare alleles may not be possible. Focussing only on marker density can be a limited strategy in indirect association studies for GxE. Cyril Dalmasso 1 , Emmanuelle Génin 2 , Catherine Bourgain 2 , Philippe Broët 148 JE 2492 , Univ. Paris-Sud, France 49 INSERM UMR-S 535 and University Paris Sud, Villejuif, France Keywords: Linkage analysis, Multiple testing, False Discovery Rate, Mixture model In the context of genome-wide linkage analyses, where a large number of statistical tests are simultaneously performed, the False Discovery Rate (FDR) that is defined as the expected proportion of false discoveries among all discoveries is nowadays widely used for taking into account the multiple testing problem. Other related criteria have been considered such as the local False Discovery Rate (lFDR) that is a variant of the FDR giving to each test its own measure of significance. The lFDR is defined as the posterior probability that a null hypothesis is true. Most of the proposed methods for estimating the lFDR or the FDR rely on distributional assumption under the null hypothesis. However, in observational studies, the empirical null distribution may be very different from the theoretical one. In this work, we propose a mixture model based approach that provides estimates of the lFDR and the FDR in the context of large-scale variance component linkage analyses. In particular, this approach allows estimating the empirical null distribution, this latter being a key quantity for any simultaneous inference procedure. The proposed method is applied on a real dataset. Arief Gusnanto 1 , Frank Dudbridge 150 MRC Biostatistics Unit, Cambridge UK Keywords: Significance, genome-wide, association, permutation, multiplicity Genome-wide association scans have introduced statistical challenges, mainly in the multiplicity of thousands of tests. The question of what constitutes a significant finding remains somewhat unresolved. Permutation testing is very time-consuming, whereas Bayesian arguments struggle to distinguish direct from indirect association. It seems attractive to summarise the multiplicity in a simple form that allows users to avoid time-consuming permutations. A standard significance level would facilitate reporting of results and reduce the need for permutation tests. This is potentially important because current scans do not have full coverage of the whole genome, and yet, the implicit multiplicity is genome-wide. We discuss some proposed summaries, with reference to the empirical null distribution of the multiple tests, approximated through a large number of random permutations. Using genome-wide data from the Wellcome Trust Case-Control Consortium, we use a sub-sampling approach with increasing density to estimate the nominal p-value to obtain family-wise significance of 5%. The results indicate that the significance level is converging to about 1e-7 as the marker spacing becomes infinitely dense. We considered the concept of an effective number of independent tests, and showed that when used in a Bonferroni correction, the number varies with the overall significance level, but is roughly constant in the region of interest. We compared several estimators of the effective number of tests, and showed that in the region of significance of interest, Patterson's eigenvalue based estimator gives approximately the right family-wise error rate. Michael Nothnagel 1 , Amke Caliebe 1 , Michael Krawczak 151 Institute of Medical Informatics and Statistics, University Clinic Schleswig-Holstein, University of Kiel, Germany Keywords: Association scans, Bayesian framework, posterior odds, genetic risk, multiplicative model Whole-genome association scans have been suggested to be a cost-efficient way to survey genetic variation and to map genetic disease factors. We used a Bayesian framework to investigate the posterior odds of a genuine association under multiplicative disease models. We demonstrate that the p value alone is not a sufficient means to evaluate the findings in association studies. We suggest that likelihood ratios should accompany p values in association reports. We argue, that, given the reported results of whole-genome scans, more associations should have been successfully replicated if the consistently made assumptions about considerable genetic risks were correct. We conclude that it is very likely that the vast majority of relative genetic risks are only of the order of 1.2 or lower. Clive Hoggart 1 , Maria De Iorio 1 , John Whittakker 2 , David Balding 152 Department of Epidemiology and Public Health, Imperial College London, UK 53 Department of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, UK Keywords: Genome-wide association analyses, shrinkage priors, Lasso Testing one SNP at a time does not fully realise the potential of genome-wide association studies to identify multiple causal variants of small effect, which is a plausible scenario for many complex diseases. Moreover, many simulation studies assume a single causal variant and so more complex realities are ignored. Analysing large numbers of variants simultaneously is now becoming feasible, thanks to developments in Bayesian stochastic search methods. We pose the problem of SNP selection as variable selection in a regression model. In contrast to single SNP tests this approach simultaneously models the effect of all SNPs. SNPs are selected by a Bayesian interpretation of the lasso (Tibshirani, 1996); the maximum a posterior (MAP) estimate of the regression coefficients, which have been given independent, double exponential prior distributions. The double exponential distribution is an example of a shrinkage prior, MAP estimates with shrinkage priors can be zero, thus all SNPs with non zero regression coefficients are selected. In addition to the commonly-used double exponential (Laplace) prior, we also implement the normal exponential gamma prior distribution. We show that use of the Laplace prior improves SNP selection in comparison with single -SNP tests, and that the normal exponential gamma prior leads to a further improvement. Our method is fast and can handle very large numbers of SNPs: we demonstrate its performance using both simulated and real genome-wide data sets with 500 K SNPs, which can be analysed in 2 hours on a desktop workstation. Mickael Guedj 1,2 , Jerome Wojcik 2 , Gregory Nuel 154 Laboratoire Statistique et Génome, Université d'Evry, Evry France 55 Serono Pharmaceutical Research Institute, Plan-les-Ouates, Switzerland Keywords: Local Replication, Local Score, Association In gene-mapping, replication of initial findings has been put forwards as the approach of choice for filtering false-positives from true signals for underlying loci. In practice, such replications are however too poorly observed. Besides the statistical and technical-related factors (lack of power, multiple-testing, stratification, quality control,) inconsistent conclusions obtained from independent populations might result from real biological differences. In particular, the high degree of variation in the strength of LD among populations of different origins is a major challenge to the discovery of genes. Seeking for Local Replications (defined as the presence of a signal of association in a same genomic region among populations) instead of strict replications (same locus, same risk allele) may lead to more reliable results. Recently, a multi-markers approach based on the Local Score statistic has been proposed as a simple and efficient way to select candidate genomic regions at the first stage of genome-wide association studies. Here we propose an extension of this approach adapted to replicated association studies. Based on simulations, this method appears promising. In particular it outperforms classical simple-marker strategies to detect modest-effect genes. Additionally it constitutes, to our knowledge, a first framework dedicated to the detection of such Local Replications. Juliet Chapman 1 , Claudio Verzilli 1 , John Whittaker 156 Department of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, UK Keywords: FDR, Association studies, Bayesian model selection As genomewide association studies become commonplace there is debate as to how such studies might be analysed and what we might hope to gain from the data. It is clear that standard single locus approaches are limited in that they do not adjust for the effects of other loci and problematic since it is not obvious how to adjust for multiple comparisons. False discovery rates have been suggested, but it is unclear how well these will cope with highly correlated genetic data. We consider the validity of standard false discovery rates in large scale association studies. We also show that a Bayesian procedure has advantages in detecting causal loci amongst a large number of dependant SNPs and investigate properties of a Bayesian FDR. Peter Kraft 157 Harvard School of Public Health, Boston USA Keywords: Gene-environment interaction, genome-wide association scans Appropriately analyzed two-stage designs,where a subset of available subjects are genotyped on a genome-wide panel of markers at the first stage and then a much smaller subset of the most promising markers are genotyped on the remaining subjects,can have nearly as much power as a single-stage study where all subjects are genotyped on the genome-wide panel yet can be much less expensive. Typically, the "most promising" markers are selected based on evidence for a marginal association between genotypes and disease. Subsequently, the few markers found to be associated with disease at the end of the second stage are interrogated for evidence of gene-environment interaction, mainly to understand their impact on disease etiology and public health impact. However, this approach may miss variants which have a sizeable effect restricted to one exposure stratum and therefore only a modest marginal effect. We have proposed to use information on the joint effects of genes and a discrete list of environmental exposures at the initial screening stage to select promising markers for the second stage [Kraft et al Hum Hered 2007]. This approach optimizes power to detect variants that have a sizeable marginal effect and variants that have a small marginal effect but a sizeable effect in a stratum defined by an environmental exposure. As an example, I discuss a proposed genome-wide association scan for Type II diabetes susceptibility variants based in several large nested case-control studies. Beate Glaser 1 , Peter Holmans 158 Biostatistics and Bioinformatics Unit, Cardiff University, School of Medicine, Heath Park, Cardiff, UK Keywords: Combined case-control and trios analysis, Power, False-positive rate, Simulation, Association studies The statistical power of genetic association studies can be enhanced by combining the analysis of case-control with parent-offspring trio samples. Various combined analysis techniques have been recently developed; as yet, there have been no comparisons of their power. This work was performed with the aim of identifying the most powerful method among available combined techniques including test statistics developed by Kazeem and Farrall (2005), Nagelkerke and colleagues (2004) and Dudbridge (2006), as well as a simple combination of ,2-statistics from single samples. Simulation studies were performed to investigate their power under different additive, multiplicative, dominant and recessive disease models. False-positive rates were determined by studying the type I error rates under null models including models with unequal allele frequencies between the single case-control and trios samples. We identified three techniques with equivalent power and false-positive rates, which included modifications of the three main approaches: 1) the unmodified combined Odds ratio estimate by Kazeem & Farrall (2005), 2) a modified approach of the combined risk ratio estimate by Nagelkerke & colleagues (2004) and 3) a modified technique for a combined risk ratio estimate by Dudbridge (2006). Our work highlights the importance of studies investigating test performance criteria of novel methods, as they will help users to select the optimal approach within a range of available analysis techniques. David Almorza 1 , M.V. Kandus 2 , Juan Carlos Salerno 2 , Rafael Boggio 359 Facultad de Ciencias del Trabajo, University of Cádiz, Spain 60 Instituto de Genética IGEAF, Buenos Aires, Argentina 61 Universidad Nacional de La Plata, Buenos Aires, Argentina Keywords: Principal component analysis, maize, ear weight, inbred lines The objective of this work was to evaluate the relationship among different traits of the ear of maize inbred lines and to group genotypes according to its performance. Ten inbred lines developed at IGEAF (INTA Castelar) and five public inbred lines as checks were used. A field trial was carried out in Castelar, Buenos Aires (34° 36' S , 58° 39' W) using a complete randomize design with three replications. At harvest, individual weight (P.E.), diameter (D.E.), row number (N.H.) and length (L.E.) of the ear were assessed. A principal component analysis, PCA, (Infostat 2005) was used, and the variability of the data was depicted with a biplot. Principal components 1 and 2 (CP1 and CP2) explained 90% of the data variability. CP1 was correlated with P.E., L.E. and D.E., meanwhile CP2 was correlated with N.H. We found that individual weight (P.E.) was more correlated with diameter of the ear (D.E.) than with length (L.E). Five groups of inbred lines were distinguished: with high P.E. and mean N.H. (04-70, 04-73, 04-101 and MO17), with high P.E. but less N.H. (04-61 and B14), with mean P.E. and N.H. (B73, 04-123 and 04-96), with high N.H. but less P.E. (LP109, 04-8, 04-91 and 04-76) and with low P.E. and low N.H. (LP521 and 04-104). The use of PCA showed which variables had more incidence in ear weight and how is the correlation among them. Moreover, the different groups found with this analysis allow the evaluation of inbred lines by several traits simultaneously. Sven Knüppel 1 , Anja Bauerfeind 1 , Klaus Rohde 162 Department of Bioinformatics, MDC Berlin, Germany Keywords: Haplotypes, association studies, case-control, nuclear families The area of gene chip technology provides a plethora of phase-unknown SNP genotypes in order to find significant association to some genetic trait. To circumvent possibly low information content of a single SNP one groups successive SNPs and estimates haplotypes. Haplotype estimation, however, may reveal ambiguous haplotype pairs and bias the application of statistical methods. Zaykin et al. (Hum Hered, 53:79-91, 2002) proposed the construction of a design matrix to take this ambiguity into account. Here we present a set of functions written for the Statistical package R, which carries out haplotype estimation on the basis of the EM-algorithm for individuals (case-control) or nuclear families. The construction of a design matrix on basis of estimated haplotypes or haplotype pairs allows application of standard methods for association studies (linear, logistic regression), as well as statistical methods as haplotype sharing statistics and TDT-Test. Applications of these methods to genome-wide association screens will be demonstrated. Manuela Zucknick 1 , Chris Holmes 2 , Sylvia Richardson 163 Department of Epidemiology and Public Health, Imperial College London, UK 64 Department of Statistics, Oxford Center for Gene Function, University of Oxford, UK Keywords: Bayesian, variable selection, MCMC, large p, small n, structured dependence In large-scale genomic applications vast numbers of markers or genes are scanned to find a few candidates which are linked to a particular phenotype. Statistically, this is a variable selection problem in the "large p, small n" situation where many more variables than samples are available. An additional feature is the complex dependence structure which is often observed among the markers/genes due to linkage disequilibrium or their joint involvement in biological processes. Bayesian variable selection methods using indicator variables are well suited to the problem. Binary phenotypes like disease status are common and both Bayesian probit and logistic regression can be applied in this context. We argue that logistic regression models are both easier to tune and to interpret than probit models and implement the approach by Holmes & Held (2006). Because the model space is vast, MCMC methods are used as stochastic search algorithms with the aim to quickly find regions of high posterior probability. In a trade-off between fast-updating but slow-moving single-gene Metropolis-Hastings samplers and computationally expensive full Gibbs sampling, we propose to employ the dependence structure among the genes/markers to help decide which variables to update together. Also, parallel tempering methods are used to aid bold moves and help avoid getting trapped in local optima. Mixing and convergence of the resulting Markov chains are evaluated and compared to standard samplers in both a simulation study and in an application to a gene expression data set. Reference Holmes, C. C. & Held, L. (2006) Bayesian auxiliary variable models for binary and multinomial regression. Bayesian Analysis1, 145,168. Dawn Teare 165 MMGE, University of Sheffield, UK Keywords: CNP, family-based analysis, MCMC Evidence is accumulating that segmental copy number polymorphisms (CNPs) may represent a significant portion of human genetic variation. These highly polymorphic systems require handling as phenotypes rather than co-dominant markers, placing new demands on family-based analyses. We present an integrated approach to meet these challenges in the form of a graphical model, where the underlying discrete CNP phenotype is inferred from the (single or replicate) quantitative measure within the analysis, whilst assuming an allele based system segregating through the pedigree. [source] Dissecting the heterogeneity of rheumatoid arthritis through linkage analysis of quantitative traitsARTHRITIS & RHEUMATISM, Issue 1 2007Lindsey A. Criswell Objective To dissect the heterogeneity of rheumatoid arthritis (RA) through linkage analysis of quantitative traits, specifically, IgM rheumatoid factor (IgM-RF) and anti,cyclic citrullinated peptide (anti-CCP) autoantibody titers. Methods Subjects, 1,002 RA patients from 491 multiplex families recruited by the North American RA Consortium, were typed for 379 microsatellite markers. Anti-CCP titers were determined based on a second-generation enzyme-linked immunosorbent assay, and IgM-RF levels were quantified by immunonephelometry. We used the Merlin statistical package to perform nonparametric quantitative trait linkage analysis. Results For each of the quantitative traits, evidence of linkage, with logarithm of odds (LOD) scores of >1.0, was found in 9 regions. For both traits, the strongest evidence of linkage was for marker D6S1629 on chromosome 6p (LOD 14.02 for anti-CCP and LOD 12.09 for RF). Six other regions with LOD scores of >1.0 overlapped between the 2 traits, on chromosomes 1p21.1, 5q15, 8p23.1, 16p12.1, 16q23.1, and 18q21.31. Evidence of linkage to anti-CCP titer but not to RF titer was found in 2 regions (chromosomes 9p21.3 and 10q21.1), and evidence of linkage to RF titer but not to anti-CCP titer was found in 2 regions (chromosomes 5p15.2 and 1q42.3). Several covariates were significantly associated with 1 or both traits, and linkage analysis exploring the covariate effects revealed striking effects of sex in modulating linkage signals for several chromosomal regions. For example, sex had a striking impact on the linkage results for both quantitative traits on chromosome 6p (P = 0.0007 for anti-CCP titer and P = 0.0012 for RF titer), suggesting a sex,HLA region interaction. Conclusion Analysis of quantitative components of RA is a promising approach for dissecting the genetic heterogeneity of this complex disorder. These results highlight the potential importance of sex or other covariates that may modulate some of the genetic effects that influence the risk of specific disease manifestations. [source] Hepatitis C virus infection rates and risk factors in an Australian hospital endoscopy cohortAUSTRALIAN AND NEW ZEALAND JOURNAL OF PUBLIC HEALTH, Issue 5 2009Karen Vickery Abstract Objective: To determine the reservoir and risk factors of HCV infection in a hospital population. Methods: The presence of anti-HCV in 2,119 endoscopy patients was related to putative risk factors for exposure using the SAS statistical package. Results: Most of the 4.7% of anti-HCV positive patients had multiple risk factors for HCV exposure. The risk was significantly increased in patients; with a previous history of hepatitis (36.4 fold), past history of injecting drugs (IDU) (32.1 fold), those born in North Africa, Middle East and Mediterranean countries (4.3 fold), had been tattooed before 1980s (3.3 fold), from 1980s-1990s (5.9 fold), had acupuncture before 1980s (3.8 fold), had a blood transfusion (3.6 fold), had clotting factors or growth hormone (4 fold), had contact with someone diagnosed with hepatitis in 1990s (4.1 fold). Of the anti-HCV patients 38 had a history of IDU, 43 were migrants and 10 were both. Conclusion: Anti-HCV prevalence was five times higher than predicted by the passive surveillance scheme and 20% of patients were unaware of their infection. Only one of these patients reported IDU. The evidence of HCV intersecting epidemics between developing and developed countries in Australia was strongly supported. Implications: The study provides a rational basis for targeted programs to identify asymptomatic HCV carriers who might benefit from the new antiviral treatment. [source] Breast cancer survivors in the United StatesCANCER, Issue 9 20092005-201, Geographic Variability, Time Trends Abstract BACKGROUND: Breast cancer continues to place a significant burden on the healthcare system. Regional prevalence measures are instrumental in the development of cancer control policies. Very few population-based cancer registries are able to provided local, long-term incidence and follow-up information that permits the direct calculation of prevalence. Model-based prevalence estimates are an alternative when this information is lacking or incomplete. The current work represents a comprehensive collection of female breast cancer prevalence from 2005 to 2015 in the United States and the District of Columbia (DC). METHODS: Breast cancer prevalence estimates were derived from state-specific cancer mortality and survival data using a statistical package called the Mortality-Incidence Analysis Model or MIAMOD. Cancer survival models were derived from the Surveillance, Epidemiology, and End Results Program data and were adjusted to represent state-specific survival. Comparisons with reported incidence for 39 states and DC had validated estimates. RESULTS: By the year 2010, 2.9 million breast cancer survivors are predicted in the US, equaling 1.85% of the female population. Large variability in prevalent percentages was reported between states, ranging from 1.4% to 2.4% in 2010. Geographic variability was reduced when calculating age-standardized prevalence proportions or cancer survivors by disease duration, including 0 to 2 years and 2 to 5 years. The residual variability in age-adjusted prevalence was explained primarily by the state-specific, age-adjusted breast cancer incidence rates. State-specific breast cancer survivors are expected to increase from 16% to 51% in the decennium from 2005 to 2015 and by 31% at the national level. CONCLUSIONS: To the authors' knowledge, the current study is the first to provide systematic estimations of breast cancer prevalence in all US states through 2015. The estimated levels and time trends were consistent with the available population-based data on breast cancer incidence, prevalence, and population aging. Cancer 2009. © 2009 American Cancer Society. [source] | ||||||||||||||||||||||||||||