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Health Impact (health + impact)
Kinds of Health Impact Terms modified by Health Impact Selected AbstractsMental health impact of Afghanistan and Iraq deployment: meeting the challenge of a new generation of veteransDEPRESSION AND ANXIETY, Issue 6 2009Charles R. Marmar M.D. First page of article [source] The impairments caused by social phobia in the general population: implications for intervention,ACTA PSYCHIATRICA SCANDINAVICA, Issue 2003R. C. KesslerArticle first published online: 29 AUG 200 Objective: Although social phobia is common, treatment remains low. In order to gauge public health implications of this low treatment, information is needed on the impairments caused by social phobia. Method: A computer literature review searched for the terms ,social anxiety disorder' and ,social phobia' in the MEDLINE and PsycLIT databases. New analyses were carried out in the US National Comorbidity Survey. Results: The literature shows that social phobia has serious effects on role functioning and quality of life. These effects are least severe for pure non-generalized social phobia and most severe for comorbid generalized social phobia with avoidant personality disorder. The most direct impairments involve social interactions and information processing errors in these interactions. Indirect effects are even more important. Three indirect effects are highlighted: effects on secondary mental (e.g. depression), substance (e.g. alcoholism) and physical (e.g. cardiovascular disease) disorders; effects on normative role transitions (e.g. educational attainment); and effects on help-seeking. Conclusion: Given the early age of onset and impacts on secondary disorders and early adult life course transitions, the greatest public health impact of increasing treatment of social phobia is likely to be achieved by developing programs targeted at early identification and treatment through schools. [source] Estimating the burden of disease attributable to illicit drug use and mental disorders: what is ,Global Burden of Disease 2005' and why does it matter?ADDICTION, Issue 9 2009Louisa Degenhardt ABSTRACT Background The estimated impact of illicit drug use and mental disorders upon population health needs to be understood because there is evidence that they produce substantial loss of life and disability, and information is needed on the comparative population health impact of different diseases and risk factors to help focus policy, service and research planning and execution. Aims To provide an overview of a global project, running since the end of 2007,Global Burden of Disease (GBD) 2005. Methods The new GBD aims to update comprehensively the findings of the first GBD exercise. It aims to provide regional and global estimates of the burden of disease attributable to hundreds of diseases, injuries and their risk factors. Groups have been assembled to provide expert advice on the parameters needed to inform these estimates; here, we provide a brief summary of the broad range of work being undertaken by the group examining illicit drug use and mental disorders. Discussion The estimates of the contribution of mental disorders and illicit drugs to GBD will inform and potentially shape the focus of researchers, clinicians and governments in the years to come. We hope that interested readers might be encouraged to submit new data or feedback on the work completed thus far, as well as the work that is still under way and yet to be completed. [source] Mouse models for genetic dissection of polygenic gastrointestinal diseasesEUROPEAN JOURNAL OF CLINICAL INVESTIGATION, Issue 2 2003S. Hillebrandt Abstract Many diseases with a major public health impact are the result of complex interactions between environmental factors and multiple genes. In the past decade, methods for genome analysis, in particular quantitative trait locus (QTL) analysis in animal models, were developed to identify and localize the genes responsible for multifactorial (polygenic) diseases; QTL analysis is based on experimental crosses between inbred strains with high and low genetic susceptibility. Recently the genes underlying several QTLs could be cloned successfully. Here we describe the impact of these genomic approaches in mice on our understanding of the multifactorial genetics of three gastrointestinal diseases related to metabolism (cholesterol cholelithiasis), development (gastroschisis), and colorectal cancer. The examples demonstrate how mouse models continue to be an invaluable tool in unravelling complex pathomechanisms and unlocking our understanding of human diseases. [source] Analysis of bacterial foodborne disease outbreaks in China between 1994 and 2005FEMS IMMUNOLOGY & MEDICAL MICROBIOLOGY, Issue 1 2007Shijie Wang Abstract To gain an understanding of the outbreaks of bacterial foodborne diseases and the subsequent health impact, we reviewed 2447 papers from journals published in China that reported 1082 bacterial foodborne disease cases occurring between 1994 and 2005. Among the 1082 outbreaks of bacterial foodborne disease for which the etiology was determined, Vibrio parahaemolyticus caused the most outbreaks, followed by Salmonella, and Clostridium botulinum led to the most deaths. Most of the outbreaks occurred between May and October, except for Clostridium botulinum, which mainly occurred in January and February. In littoral provinces, Vibrio parahaemolyticus caused the most events, whereas in inland provinces, the largest percentage of events was caused by Salmonella. This review provides a background and analysis of Chinese foodborne disease caused by bacteria. We hope that this review can be compared to reviews from other regions of the world, in an attempt to prevent future outbreaks from occurring. [source] Thiazolidinedione derivatives in diabetes and cardiovascular disease: an updateFUNDAMENTAL & CLINICAL PHARMACOLOGY, Issue 3 2008Pantelis A. Sarafidis Abstract As the incidence and the public health impact of type 2 diabetes are constantly rising, treatment of hyperglycemia, prevention of diabetes-related complications are currently top medical priorities. Within the last decade several new classes of oral hypoglycemic agents were added to our armamentarium against diabetes. Among these new classes, the group of thiazolidinediones, which act through reduction of insulin resistance is perhaps the most widely used. For about 20 years, numerous background and clinical studies have evaluated the beneficial and adverse effects of these compounds. Current knowledge suggests that thiazolidinediones are as effective as metformin or sulfonylurea derivatives in improving glycemic control and exert several other beneficial metabolic and vascular effects, such as improvement in lipid profile, blood pressure lowering, redistribution of body fat away from the central compartment, microalbuminuria regression, reduction in subclinical vascular inflammation and others. On the other hand, currently used thiazolidinediones have well-established side effects, most important of which are fluid retention leading to weight gain and heart failure deterioration. Further, in the expectance of proper outcome studies to clarify the effects of these agents in cardiovascular morbidity and mortality, data from recent meta-analyses suggest that rosiglitazone may increase the risk for some cardiovascular outcomes. This article will discuss all the above issues attempting to provide an updated overview of this expanding field. [source] A health inequalities perspective on violence against womenHEALTH & SOCIAL CARE IN THE COMMUNITY, Issue 2 2007Cathy Humphreys PhD BSocWk Abstract The present paper argues that the physical and mental health consequences of gender-based violence constitute a major public health problem in the UK and a source of significant health inequality. The concept of violence against women is explored alongside brief examples of the mental and physical health impact of this violence. While the impact on women's health is relatively uncontested, the extent to which social divisions such as poverty, class and minority ethnic status create specific vulnerabilities to violence are more controversial. A widely held view within the movement to support survivors within the UK has been that violence against women cuts across class and ethnicity, and is found in all communities and classes. A more nuanced discussion of the way in which poverty and ethnic background may create particular vulnerabilities is explored. Disentangling cause and consequence, and also the barriers to help-seeking for minority ethnic women are discussed. The role of social workers in addressing the way in which violence against women is both ubiquitous but marginal in their caseloads is discussed, and appropriate interventions to respond to health inequality issues are proposed. [source] A review of the potential impact of dietary endocrine disrupters on the consumerINTERNATIONAL JOURNAL OF FOOD SCIENCE & TECHNOLOGY, Issue 5 2002Ian Shaw Endocrine disrupters, in particular xenoestrogens, have been implicated in a broad array of environmental effects. Their presence in food, either as natural components (e.g. phytoestrogens) or chemical contaminants (e.g. xenoestrogenic pesticides) have been implicated in a number of human effects (e.g. declining sperm count). We present calculations which ranks the importance of the different classes of dietary endocrine disrupters, and show that only phytoestrogens are likely to have a health impact. [source] Evaluation of stress- and immune-response biomarkers in Atlantic salmon, Salmo salar L., fed different levels of genetically modified maize (Bt maize), compared with its near-isogenic parental line and a commercial suprex maizeJOURNAL OF FISH DISEASES, Issue 4 2007A Sagstad Abstract The present study was designed to evaluate if genetically modified (GM) maize (Bt maize, event MON810) compared with the near-isogenic non-modified (nGM) maize variety, added as a starch source at low or high inclusions, affected fish health of post-smolt Atlantic salmon, Salmo salar L. To evaluate the health impact, selected stress- and immune-response biomarkers were quantified at the gene transcript (mRNA) level, and some also at the protein level. The diets with low or high inclusions of GM maize, and its near-isogenic nGM parental line, were compared to a control diet containing GM-free suprex maize (reference diet) as the only starch source. Total superoxide dismutase (SOD) activity in liver and distal intestine was significantly higher in fish fed GM maize compared with fish fed nGM maize and with the reference diet group. Fish fed GM maize showed significantly lower catalase (CAT) activity in liver compared with fish fed nGM maize and to the reference diet group. In contrast, CAT activity in distal intestine was significantly higher for fish fed GM maize compared with fish fed reference diet. Protein level of heat shock protein 70 (HSP70) in liver was significantly higher in fish fed GM maize compared with fish fed the reference diet. No diet-related differences were found in normalized gene expression of SOD, CAT or HSP70 in liver or distal intestine. Normalized gene expression of interleukin-1 beta in spleen and head-kidney did not vary significantly between diet groups. Interestingly, fish fed high GM maize showed a significantly larger proportion of plasma granulocytes, a significantly larger sum of plasma granulocyte and monocyte proportions, but a significantly smaller proportion of plasma lymphocytes, compared with fish fed high nGM maize. In conclusion, Atlantic salmon fed GM maize showed some small changes in stress protein levels and activities, but none of these changes were comparable to the normalized gene expression levels analysed for these stress proteins. GM maize seemed to induce significant changes in white blood cell populations which are associated with an immune response. [source] Tobacco use, cancer causation and public health impactJOURNAL OF INTERNAL MEDICINE, Issue 6 2002H. Kuper Abstract.,Kuper H, Adami H-O, Boffetta P (University College London, Torrington Place, London, UK; Karolinska Institutet, Stockholm, Sweden; and International Agency for Research on Cancer, Lyon, France). Tobacco use, cancer causation and public health impact. J Intern Med 2002; 251: 455,466. This review describes global patterns of tobacco use and the mechanisms by which tobacco use is involved in carcinogenesis. A second part will discuss the association between tobacco use and risk of specific cancer types. To bacco use has traditionally been a practice of high-income countries, but it has recently been taken up in low-income countries and it is particularly common in men. A wide variety of tobacco products exist, of which cigarettes are most frequently consumed. Tobacco products contain more than 50 established or identified carcinogens and these may increase risk of cancer by causing mutations that disrupt cell cycle regulation, or through their effect on the immune or endocrine systems. Certain factors such as genes, diet and environmental exposures may alter susceptibility to cancer in tobacco users. Today at least 15% of all cancers are estimated to be attributable to smoking, but this figure is expected to increase because of the uptake of tobacco use in low-income countries. [source] Biological foundation for periodontitis as a potential risk factor for atherosclerosisJOURNAL OF PERIODONTAL RESEARCH, Issue 1 2005Yong-Hee P. Chun Objectives:, Links between periodontal diseases and systemic diseases have been well documented by epidemiological studies. Recently, research has shifted to elucidating the biologic mechanism for a causal relationship. One focus of interest is atherosclerosis, the underlying event of cardiovascular diseases due to its serious health impact. However, it is still not clear whether periodontopathic pathogens are truly etiologic agents or ubiquitous bystanders. This article reviews the current understanding about the molecular biological interactions between periodontal disease and atherosclerosis and the biological plausibility of periodontitis as a potential risk factor for cardiovascular disease. Materials and methods:, The current literature regarding periodontal diseases and atherosclerosis and coronary vascular disease was searched using the Medline and PubMed databases. Results:,In vitro experiments and animal models are appropriate tools to investigate the biological interactions between periodontal disease and atherosclerosis at the cell molecular level. The concepts linking both pathologies refer to inflammatory response, immune responses, and hemostasis. In particular, Porphyromonas gingivalis appears to have unique, versatile pathogenic properties. Whether or not these findings from isolated cells or animal models are applicable in humans with genetic and environmental variations is yet to be determined. Likewise, the benefit from periodontal therapy on the development of atherosclerosis is unclear. Approaches targeting inflammatory and immune responses of periodontitis and atherosclerosis simultaneously are very intriguing. Conclusion:, An emerging concept suggests that a pathogenic burden from different sources might overcome an individual threshold culminating in clinical sequela. P. gingivalis contributes directly and indirectly to atherosclerosis. [source] Relationship between Oral Health-Related Quality of Life, Satisfaction, and Personality in Patients with Prosthetic RehabilitationsJOURNAL OF PROSTHODONTICS, Issue 1 2010FDS RCS (England), Jordanian Board, Mahmoud K. AL-Omiri BDS Abstract Purpose: This study investigated the relationship between oral health-related quality of life, satisfaction with dentition, and personality profiles among patients with fixed and/or removable prosthetic rehabilitations. Materials and Methods: Thirty-seven patients (13 males, 24 females; mean age 37.6 ± 13.3 years) with fitted prosthetic rehabilitations and 37 controls who matched the patients by age and gender were recruited into the study. The Dental Impact on Daily Living (DIDL) questionnaire was used to assess dental impacts on daily living and satisfaction with the dentition. The Oral Health Impact Profile (OHIP) was used to measure self-reported discomfort, disability, and dysfunction caused by oral conditions. Oral health-related quality of life was assessed by the United Kingdom Oral Health-Related Quality of Life (OHQoL-UK) measure. Moreover, the NEO five-factor inventory was used to assess participants' personality profiles. Results: Prosthetic factors had no relationship to the DIDL, OHIP, and OHQoL-UK scores. Patients with the least oral health impacts had better oral health-related quality of life (p= 0.023, r =,0.37), higher levels of total satisfaction, and satisfaction with appearance, pain, oral comfort, general performance, and eating (p < 0.05, r =,0.79, ,0.35, ,0.59, ,0.56, ,0.58, and ,0.50, respectively). Patients with better oral health-related quality of life (QoL) had higher total satisfaction, satisfaction with oral comfort, general performance, and eating (p < 0.05, r = 0.34, 0.39, 0.33, and 0.37, respectively). Patients with lower neuroticism scores had less oral health impact (p= 0.006, r = 0.44), better oral health-related QoL (p= 0.032, r =,0.35), higher total satisfaction, satisfaction with appearance, pain, oral comfort, and eating (p < 0.05, r =,0.58, ,0.35, ,0.33, ,0.39, and ,0.35, respectively). Conclusion: Patients' satisfaction with their dentition and prosthetic rehabilitations has positive effects on oral health-related QoL and oral health impacts and improves patients' daily living and dental perceptions. Neuroticism might influence and predict patients' satisfaction with their dentition, oral health impacts, and oral health-related QoL. Satisfaction with the dentition might predict a patient's level of neuroticism. [source] The impact of reported direct and indirect killing on mental health symptoms in Iraq war veterans,JOURNAL OF TRAUMATIC STRESS, Issue 1 2010Shira Maguen This study examined the mental health impact of reported direct and indirect killing among 2,797 U.S. soldiers returning from Operation Iraqi Freedom. Data were collected as part of a postdeployment screening program at a large Army medical facility. Overall, 40% of soldiers reported killing or being responsible for killing during their deployment. Even after controlling for combat exposure, killing was a significant predictor of posttraumatic disorder (PTSD) symptoms, alcohol abuse, anger, and relationship problems. Military personnel returning from modern deployments are at risk of adverse mental health conditions and related psychosocial functioning related to killing in war. Mental health assessment and treatment should address reactions to killing to optimize readjustment following deployment. [source] Applying the Systematic Screening and Assessment Method to childhood obesity preventionNEW DIRECTIONS FOR EVALUATION, Issue 125 2010Nicola Dawkins The authors describe application of the Systematic Screening and Assessment (SSA) Method to an initiative called the Early Assessment of Programs and Policies to Prevent Childhood Obesity. Over a 2-year period, a national network of practitioners, policy makers, and funders nominated programs and policies across five substantive areas: school district local wellness policies, school-based comprehensive physical activity programs, day care and after-school programs, access to healthy foods in low-income communities, and changes in the built environment to promote physical activity. The role of an expert panel in selecting innovations for evaluability assessment on the basis of the likelihood for a positive health impact is described. © Wiley Periodicals, Inc., and the American Evaluation Association. [source] A public health collaboration for the surveillance of autism spectrum disordersPAEDIATRIC & PERINATAL EPIDEMIOLOGY, Issue 2 2007Catherine E. Rice Summary Autism spectrum disorders (ASDs) represent a range of behavioural phenotypes defined by impaired development in social interaction, communication, imagination, and range of interests or behaviours. The aetiology and epidemiology of these serious developmental disabilities (DDs) are poorly understood. Estimates of the population prevalence of ASDs have varied widely within the US and abroad, with increasing estimates in most of the recent studies. In an effort to improve our understanding of the prevalence, population characteristics and public health impact of these conditions, the Centers for Disease Control and Prevention has funded a multi-site surveillance network for ASDs and other DDs that consists of programmes known as the Autism and Developmental Disabilities Monitoring (ADDM) network which conducts surveillance activities and the Centers for Autism and Developmental Disabilities Research and Epidemiology (CADDRE) which also conducts surveillance in addition to special research studies related to the ASDs. This collaboration will be referred to hereafter as the ADDM Network. The ADDM Network is implementing a multiple-source surveillance programme to determine population prevalence and characteristics of ASDs and other DDs. This paper describes the collaborative efforts and explains the methods in developing this coordinated public health surveillance network to provide an ongoing source of high-quality data on ASDs. [source] Web-based Health Survey Systems in Outcome Assessment and Management of PainPAIN MEDICINE, Issue 2007Vinod K. Podichetty MD ABSTRACT Pain is a complex phenomenon lacking a well-defined paradigm for diagnosis and management across medical disciplines. This is due in part to inconsistencies in the assessment of pain as well as in the measurement of related social and psychological states. Efforts to evaluate and measure pain through objective tests have been hindered by challenges such as methodological differences in data acquisition, and the lack of common, universally accepted information systems. Physicians and hospital administrators have expressed mixed reactions to the costs that inevitably accompany advances in medical technology. Nonetheless, computer systems are currently being developed for use in the quantitative assessment and management of pain, which can advance our understanding of the public health impact of pain, improve the care individual patients receive, and educate providers. The description of an interdisciplinary, integrated, health survey system illustrates the approach and highlights the advantages of using information technology in pain evaluation and management. [source] The incidence of immune thrombocytopenic purpura in children and adults: A critical review of published reports,AMERICAN JOURNAL OF HEMATOLOGY, Issue 3 2010Deirdra R. Terrell Reports of the incidence of ITP are few and their methodology is variable. Accurate estimates of the incidence of immune thrombocytopenic purpura (ITP) are important to understand the medical and public health impact of the disease. To critically review all published reports on the incidence of ITP in children and adults, all articles identified on the Medline database (searched January 1, 1966-August 7, 2009) that reported data on the incidence of ITP were retrieved. Articles which directly estimated the incidence of ITP were selected for review. Eight articles reported the incidence of acute ITP in children. After review, four were determined to have the strongest estimates, based on the method of patient identification and study design. The lowest incidence estimate in these four studies was 2.2 per 105 children/year (95% confidence interval 1.9, 2.4) and the highest incidence estimate was 5.3 per 105 children/year (95% confidence interval 4.3, 6.4). Three studies reported the incidence of ITP in adults. The estimate from the article with the strongest methodology reported an incidence estimate of 3.3 per 105 adults/year. The current strongest estimate of the incidence of acute ITP in children is between 1.9 and 6.4 per 105 children/year; for adults the current strongest estimate of the incidence of ITP is 3.3 per 105 adults/year. An important limitation of these studies is that they are primarily from Europe and may not be generalizable to all regions. Am. J. Hematol. 2010. © 2009 Wiley-Liss, Inc. [source] International study of wheezing in infants: risk factors in affluent and non-affluent countries during the first year of lifePEDIATRIC ALLERGY AND IMMUNOLOGY, Issue 5 2010Luis Garcia-Marcos Garcia-Marcos L, Mallol J, Solé D, Brand PLP and EISL group. International study of wheezing in infants: risk factors in affluent and non-affluent countries during the first year of life. Pediatr Allergy Immunol 2010: 21: 878,888. © 2010 John Wiley & Sons A/S Risk factors for wheezing during the first year of life (a major cause of respiratory morbidity worldwide) are poorly known in non-affluent countries. We studied and compared risk factors in infants living in affluent and non-affluent areas of the world. A population-based study was carried out in random samples of infants from centres in Latin America (LA) and Europe (EU). Parents answered validated questionnaires referring to the first year of their infant's life during routine health visits. Wheezing was stratified into occasional (1,2 episodes, OW) and recurrent (3 + episodes, RW). Among the 28687 infants included, the most important independent risk factors for OW and RW (both in LA and in EU) were having a cold during the first 3 months of life [OR for RW 3.12 (2.60,3.78) and 3.15 (2.51,3.97); population attributable fraction (PAF) 25.0% and 23.7%]; and attending nursery school [OR for RW 2.50 (2.04,3.08) and 3.09 (2.04,4.67); PAF 7.4% and 20.3%]. Other risk factors were as follows: male gender, smoking during pregnancy, family history of asthma/rhinitis, and infant eczema. Breast feeding for >3 months protected from RW [OR 0.8 (0.71,0.89) in LA and 0.77 (0.63,0.93) in EU]. University studies of mother protected only in LA [OR for OW 0.85 (0.76,0.95) and for RW 0.80 (0.70,0.90)]. Although most risk factors for wheezing are common in LA and EU; their public health impact may be quite different. Avoiding nursery schools and smoking in pregnancy, breastfeeding babies >3 months, and improving mother's education would have a substantial impact in lowering its prevalence worldwide. [source] Emergency department visits attributed to selected analgesics, United States, 2004,2005,PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, Issue 3 2009Mary Willy PhD Abstract Purpose To estimate the rate of emergency department (ED) visits attributed to selected analgesic-containing medications. Methods We used a nationally representative public health surveillance system to provide estimates of adverse events identified in EDs, and a national telephone survey to provide estimates of selected analgesic-containing medication usage in the US population, 2004,2005. Analysis was restricted to products containing acetaminophen, aspirin, ibuprofen, or naproxen. Types of adverse events and outcomes were compared. Estimated numbers and rates of ED visits were calculated by analgesic groupings and patient age groups. Results The estimated overall rate of ED visits attributed to analgesic-containing medications was 1.6 visits /100,000 users per week. The very old and very young had the highest rates; there were minimal differences in rates by patient gender. Acetaminophen was the attributed drug with the most estimated ED visits and generally had the highest rates of ED visits. The highest estimated rate for a specific product group was among subjects 18,64 years of age taking narcotic-acetaminophen products (8.9 ED visits /100,000 users per week). Overall, 12% of patients presenting to EDs with analgesic-attributed events were hospitalized. Conclusions Rates of ED visits due to analgesics vary depending on the age of the patient and the product; most do not result in hospitalization. Although the rate of emergency visits is relatively low, because of the wide use of the analgesics, public health impact is considerable. Copyright © 2009 John Wiley & Sons, Ltd. [source] Quantitative assessment of the gastrointestinal and cardiovascular risk-benefit of celecoxib compared to individual NSAIDs at the population level,,PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, Issue 4 2007Cristina Varas-Lorenzo MD Abstract Purpose To estimate the net cardiovascular (CV) (coronary heart disease, stroke, congestive heart failure), and gastrointestinal (GI) (peptic ulcer complications) risk-benefit public health impact of the use of celecoxib compared to non-selective NSAIDs in the arthritis population. Methods We applied discrete event simulation models to data from the US National Health Surveys, CV risk-prediction models from the Framingham Heart Study, and population-based studies. Models took into account the multifactorial effect of risk factors, comorbidity, and competing risk of mortality. We simulated the natural history of CV and GI disease in the U.S. arthritis population over 1 year, through the individual baseline cardiovascular and gastrointestinal risk profile. This model was modified with relative risks associated with the use of each treatment. The mean number of events was estimated for each end-point in each model: natural history, celecoxib, diclofenac, ibuprofen, naproxen. The number of events for celecoxib was compared with each NSAID. Results The evaluation included 1% of the U.S. population with arthritis. Celecoxib, when applied to 100,000 patients over 1 year, resulted in 570 (range from sensitivity analysis: 440,691), 226 (124,313), and 746 (612,868) fewer ulcer complications than diclofenac, ibuprofen, and naproxen, respectively. There were 20 (16,25), 8 (4,12), and 27 (22,32) fewer deaths from ulcer complications, respectively. No increase in cardiovascular events or all cause mortality was observed for celecoxib versus the other individual NSAIDs. Conclusion Results from these simulations suggest a gastrointestinal benefit for celecoxib not offset by increased cardiovascular events or mortality. The methodology used here provides a risk-benefit assessment framework for evaluating the public heath impact of drugs. Copyright © 2006 John Wiley & Sons, Ltd. [source] Immigration, employment relations, and health: Developing a research agendaAMERICAN JOURNAL OF INDUSTRIAL MEDICINE, Issue 4 2010Joan Benach Abstract Background International migration has emerged as a global issue that has transformed the lives of hundreds of millions of persons. Migrant workers contribute to the economic growth of high-income countries often serving as the labour force performing dangerous, dirty and degrading work that nationals are reluctant to perform. Methods Critical examination of the scientific and "grey" literatures on immigration, employment relations and health. Results Both lay and scientific literatures indicate that public health researchers should be concerned about the health consequences of migration processes. Migrant workers are more represented in dangerous industries and in hazardous jobs, occupations and tasks. They are often hired as labourers in precarious jobs with poverty wages and experience more serious abuse and exploitation at the workplace. Also, analyses document migrant workers' problems of social exclusion, lack of health and safety training, fear of reprisals for demanding better working conditions, linguistic and cultural barriers that minimize the effectiveness of training, incomplete OHS surveillance of foreign workers and difficulty accessing care and compensation when injured. Therefore migrant status can be an important source of occupational health inequalities. Conclusions Available evidence shows that the employment conditions and associated work organization of most migrant workers are dangerous to their health. The overall impact of immigration on population health, however, still is poorly understood and many mechanisms, pathways and overall health impact are poorly documented. Current limitations highlight the need to engage in explicit analytical, intervention and policy research. Am. J. Ind. Med. 53:338,343, 2010. © 2009 Wiley-Liss, Inc. [source] Gastroschisis: International epidemiology and public health perspectives,AMERICAN JOURNAL OF MEDICAL GENETICS, Issue 3 2008Eduardo E. Castilla Abstract Gastroschisis offers the intriguing epidemiological situation of a pandemic, strongly associated with very low maternal age. Identifying gastroschisis, and distinguishing it from the other abdominal wall defects, is theoretically easy but difficult in practice. The baseline birth prevalence of gastroschisis before the pandemic was approximately 1 in 50,000 births and has increased since between 10- and 20-fold. In many populations worldwide, it is still increasing. Such increasing prevalence and the association with very low maternal age are well proven, but the interaction between these two findings remains unknown. Geographic gradients (decreasing prevalence from North to South) are clear in Continental Europe and suggestive in Britain and Ireland. Gastroschisis seems more frequent in Caucasians compared to African Blacks and Orientals, and in Northern compared to Southern Europeans. These observations indicate the need for investigating gene,environment interactions. Since the global human situation is marked by inequalities among as well as within countries, the medical care and public health impact of gastroschisis varies widely among regions and social strata. The postnatal benefits of prenatal diagnosis of gastroschisis include family awareness; adequate planning of delivery with alerted obstetrical, pediatric, and surgical staff; optimal risk categorization, and personalized protocol for action. The increasing prevalence of gastroschisis combined with improved medical techniques to reduce morbidity and mortality are also increasing the burden and costs of this anomaly on health systems. © 2008 Wiley-Liss, Inc. [source] Prevalence of Dementia Among the Elderly in a Japanese Community Population,Comparative Study on the 1983 and 1996 Survey: The Aichi StudyPSYCHOGERIATRICS, Issue 4 2001Hiroto Shibayama Background:An epidemiological survey of dementia among community residents over 65 years of age in Aichi Prefecture (Japan) was conducted in 1983 and 1996. We compared the prevalence rates of dementia in 1996, with the previously published rates of 1983. Methods:The study employed a two-stage design. First stage: A test based on the DSM-III-R criteria for dementia was administered to all participating residents, who were randomly drawn from the resident register (856,879) of Aichi Prefecture in 1995 (495,923 in 1983). Second stage: A detailed clinical and cognitive evaluation (including MMSE and neurological examination) of the subjects identified in the first stage was carried out by trained psychiatrists. Results:The prevalence rate for dementia in 1996 was 4.8% (moderate and severe 2.1%) compared with 5.8% (2.2%) in 1983; for senile dementia of Alzheimer type (SDAT) it was 2.8% in 1996 and 2.4% in 1983; for cerebrovascular dementia (CVD), 1.8% in 1996 and 2.8% in 1983. Conclusion:Up to this time, the cases of CVD have been more frequent than those of SDAT in Japan, especially in the urban areas. However, the relationship between CVD and SDAT has now reversed. These data suggest that SDAT is a common condition and that its public health impact will continue to increase with the increasing longevity of the population in Japan. [source] Process of Care Events in Transplantation: Effects on the Cost of HospitalizationAMERICAN JOURNAL OF TRANSPLANTATION, Issue 10 2010N. N. Egorova Deviations in the processes of healthcare delivery that affect patient outcomes are recognized to have an impact on the cost of hospitalization. Whether deviations that do not affect patient outcome affects cost has not been studied. We have analyzed process of care (POC) events that were reported in a large transplantation service (n = 3,012) in 2005, delineating whether or not there was a health consequence of the event and assessing the impact on hospital resource utilization. Propensity score matching was used to adjust for patient differences. The rate of POC events varied by transplanted organ: from 10.8 per 1000 patient days (kidney) to 17.3 (liver). The probability of a POC event increased with severity of illness. The majority (81.5%) of the POC events had no apparent effect on patients' health (63.6% no effect and 17.9% unknown). POC events were associated with longer length of stay (LOS) and higher costs independent of whether there was a patient health impact. Multiple events during the same hospitalization were associated with the highest impact on LOS and cost. POC events in transplantation occur frequently, more often in sicker patients and, although the majority of POC events do not harm the patient, their effect on resource utilization is significant. [source] Alcohol, Tobacco, and Other Drugs: Future Directions for Screening and Intervention in the Emergency DepartmentACADEMIC EMERGENCY MEDICINE, Issue 11 2009Rebecca M. Cunningham MD Abstract This article is a product of a breakout session on injury prevention from the 2009 Academic Emergency Medicine consensus conference on "Public Health in the ED: Screening, Surveillance, and Intervention." The emergency department (ED) is an important entry portal into the medical care system. Given the epidemiology of substance use among ED patients, the delivery of effective brief interventions (BIs) for alcohol, drug, and tobacco use in the ED has the potential to have a large public health impact. To date, the results of randomized controlled trials of interventional studies in the ED setting for substance use have been mixed in regard to alcohol and understudied in the area of tobacco and other drugs. As a result, there are more questions remaining than answered. The work group developed the following research recommendations that are essential for the field of screening and BI for alcohol, tobacco, and other drugs in the ED. 1) Screening,develop and validate brief and practical screening instruments for ED patients and determine the optimal method for the administration of screening instruments. 2) Key components and delivery methods for intervention,conduct research on the effectiveness of screening, brief intervention, and referral to treatment (SBIRT) in the ED on outcomes (e.g., consumption, associated risk behaviors, and medical psychosocial consequences) including minimum dose needed, key components, optimal delivery method, interventions focused on multiple risk behaviors and tailored based on assessment, and strategies for addressing polysubstance use. 3) Effectiveness among patient subgroups,conduct research to determine which patients are most likely to benefit from a BI for substance use, including research on moderators and mediators of intervention effectiveness, and examine special populations using culturally and developmentally appropriate interventions. 4) Referral strategies,a) promote prospective effectiveness trials to test best strategies to facilitate referrals and access from the ED to preventive services, community resources, and substance abuse and mental health treatment; b) examine impact of available community services; c) examine the role of stigma of referral and follow-up; and d) examine alternatives to specialized treatment referral. 5) Translation,conduct translational and cost-effectiveness research of proven efficacious interventions, with attention to fidelity, to move ED SBIRT from research to practice. [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 Bonaďti-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 naďve 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] Possible health impact of phytoestrogens and xenoestrogens in food,APMIS, Issue 3 2001Dolores Ibarreta Plants produce estrogen-like substances, denominated phytoestrogens, which are present in many human foodstuffs. The consumption of phytoestrogens has been associated with a variety of protective effects. Their relative estrogenic potency combined with their concentrations in food and human plasma indicate biological relevance. However, their biological properties differ from those of estradiol or other endogenous estrogens in humans. For instance, their possible effects on SHBG, inhibition of steroid metabolizing enzymes, anti-proliferative and anti-angiogenetic and other side effects have been described. Furthermore, phytoestrogens can exert estrogenic and antiestrogenic activities at the same time and their potency and metabolism have not been yet elucidated in all cases. In recent decades growing evidence has accumulated on the hormone-like effects of synthetic chemicals that appeared in the environment. The possible impact of xenoestrogens, to which humans are also exposed through the food chain, needs to be further clarified as well. The molecular effects and control mechanisms of these substances, their pharmacokinetics, threshold levels and dose-response differences are issues that require further research before a full assessment of their effect on humans can be drawn. Evaluating the total exposure and impact of this estrogenic effect is very challenging because of the lack of specific knowledge in some areas and the differences in the biological activity among these substances, as pinpointed in this review. [source] The Sydney Medically Supervised Injecting Centre: a controversial public health measureAUSTRALIAN AND NEW ZEALAND JOURNAL OF PUBLIC HEALTH, Issue 6 2002Cate Kelly Background: Injecting drug use remains a major public health concern, particularly because of opiate overdose and transmission of blood-borne viruses. Sydney's Medically Supervised Injecting Centre (MSIC) opened on a trial basis in May 2001 in an effort to reduce the harms of drug use. In this report, we provide a brief overview of the reported public health impact of supervising injecting facilities (SIFs) and review the history and early process evaluations of the Sydney Centre. Methods Medline, Internet searches and perusal of bibliographies of articles were used to identify key English language publications on SIFs. These were supplemented by interview with the Medical Director of Sydney MSIC, Dr Ingrid van Beek. Discussion and conclusions: It is difficult to be certain of the public health impact of SIFs but evidence from overseas and Sydney's early process evaluations provide promise that they may make a positive contribution to health. [source] Mental health impact for adolescents living with prolonged droughtAUSTRALIAN JOURNAL OF RURAL HEALTH, Issue 1 2010John G. Dean Abstract Background:,A 2004 study showed adolescents living in rural Australia were aware of the impact of drought on self, family and community, but did not report levels of emotional distress higher than adolescents of similar age and gender in the Australian community. It was proposed that the rural lifestyle had helped adolescents build resilience for managing this environmental adversity. Objective:,To re sample adolescents from the same rural area and determine if this resilience remained after ongoing drought three years later. Design:,A mixed methods approach using focus groups and a self-report questionnaire. Setting:,Government Central Schools within the Riverina region of New South Wales. Participants:,Male and female adolescents (n = 111) aged 11,17 years completed the self-report questionnaires, while some adolescents (n = 61) within this group also participated in focus groups. Main outcome measure:,The Strengths and Difficulties Questionnaire and a Drought and Community Survey for Children comprised the self-report survey. Results:,Adolescents reported significantly higher levels of emotional distress than those in the previous study (t (191) = 2.80, P < 0.01) and 12% of adolescents scored in the clinical caseness range. Thematic analysis showed consistency with the previous study as well as new themes of grief, loss and the impacts of global climate change. Conclusions:,Results indicate a reporting of lesser well-being than was reported by a comparable group of young people four years earlier. A preventative intervention with a focus on family and community is recommended to address the mental health of adolescents enduring a chronic environmental adversity such as drought. [source] Thirty-five years in bioelectromagnetics researchBIOELECTROMAGNETICS, Issue 1 2007C-K. Chou Abstract For 35 years, I have been involved in various bioelectromagnetics research projects including acute and long-term radiofrequency (RF) bioeffects studies, dosimetry, exposure systems, MRI safety, cancer studies involving hyperthermia and electrochemical treatment, development of RF exposure and measurement standards, and product compliance. My first study demonstrated that effects on isolated nerve and muscle preparations were due to thermal effects of RF exposure. The recording of cochlear microphonics in animals shows the mechanical nature of the microwave auditory effect. In 1992, we published the results of a large-scale lifetime study in which 100 rats were sham-exposed and 100 rats were exposed for 21 h/day for 25 months to a pulsed RF signal. In dosimetry studies, human models were employed as well as many animal species including mice, rats, rabbits, monkeys, and birds of many sizes. Cancer hyperthermia studies demonstrated that knowledge of temperature distribution was crucial for successful treatment. Research on electrochemical treatment of tumors with direct current involved cellular, animal, and clinical studies. Over the past few decades, there has been rather extensive investigation of the public health impact of RF exposure. In my opinion, future research in bioelectromagnetics should place greater emphasis on medical applications. Bioelectromagnetics © 2006 Wiley-Liss, Inc. [source] | |||||||||||||||||||||||||||||||||||||