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Therapeutics
Kinds of Therapeutics Selected AbstractsUnlocking the opportunity of tight glycaemic controlDIABETES OBESITY & METABOLISM, Issue 2005Innovative delivery of insulin via the lung As the incidence of diabetes reaches epidemic proportions, the use of new, alternative routes of insulin delivery to manage glycaemic control is becoming an ever more active area of research. The high permeability and large surface area of the lung make it an attractive alternative to subcutaneous (SC) insulin injections. This review discusses the technical factors that influence the efficacy of pulmonary drug delivery and describes how an appreciation of these issues has enabled the design of Exubera®, a novel, non-invasive, pulmonary dry-powder human insulin delivery system currently in development by Pfizer and the sanofi-aventis Group in collaboration with Nektar Therapeutics. While clinical trials of this novel aerosol delivery of insulin are still ongoing in patients with diabetes, the results so far suggest it is simple to use and can provide reproducible doses of insulin in therapeutic amounts with only a few inhalations per dose. In addition, it has been shown to be comparable in terms of efficacy and safety to a conventional SC insulin injection regimen. Delivering aerosolized drugs via the lungs avoids the necessity for SC injections and thereby may increase the patient's acceptability of an insulin-based therapeutic regimen. [source] Therapeutics for alcoholism: what's the future?DRUG AND ALCOHOL REVIEW, Issue 1 2007ANDREW J. LAWRENCE Abstract As with other addictions, human alcoholism is characterised as a chronically relapsing condition. Consequently, the therapeutic goal is the development of clinically effective, safe drugs that promote high adherence rates and prevent relapse. These products can then be used in conjunction with psychosocial approaches. In this review, preclinical studies are highlighted that indicate the mechanism of action of currently used anti-craving medications or demonstrate the potential of novel pharmacological agents for the treatment of alcohol use disorders. While current pharmacological strategies are far from ideal, there are a number of candidate molecules that may ultimately be developed into therapeutic agents. In addition, prescribing clinicians should also consider strategies such as combinations of various drugs to aid in the regulation of aberrant alcohol consumption. [source] Therapy Discovery for Pharmacoresistant Epilepsy and for Disease-modifying Therapeutics: Summary of the NIH/NINDS/AES Models II WorkshopEPILEPSIA, Issue 12 2003James P. Stables First page of article [source] Goodman and Gilman's the Pharmacological Basis of TherapeuticsFOCUS ON ALTERNATIVE AND COMPLEMENTARY THERAPIES AN EVIDENCE-BASED APPROACH, Issue 2 2002J Thompson Coon [source] The Washington Manual of Ambulatory TherapeuticsJOURNAL OF ADVANCED NURSING, Issue 6 2004Nadine Abelson-Mitchell No abstract is available for this article. [source] Humanizing a Mouse Gene for Human Therapeutics: Lessons From Denosumab,JOURNAL OF BONE AND MINERAL RESEARCH, Issue 2 2009David Graham Little No abstract is available for this article. [source] Vignettes in Osteoporosis: A Road Map to Successful Therapeutics,JOURNAL OF BONE AND MINERAL RESEARCH, Issue 1 2004Clifford J Rosen Abstract The diagnosis and management of osteoporosis have become increasingly more complex as new drugs enter the marketplace and meta-analyses of randomized trials with "other" agents become more prolific. We describe five common clinical scenarios encountered in the practice of osteoporosis medicine and various road maps that could lead to successful therapy. Introduction: The diagnosis and treatment of osteoporosis have changed dramatically in the last decade. Advances in diagnostic technologies and a range of newer treatment options have provided the clinician with a wide array of choices for treating this chronic disease. Despite the issuance of several "guidelines" and practice recommendations, there still remains confusion among clinicians about basic approaches to the management of osteoporosis. This paper should be used as a case-based approach to define optimal therapeutic choices. Materials and Methods: Five representative cases were selected from two very large clinical practices (Bangor, ME; Pittsburgh, PA). Diagnostic modalities and treatment options used in these cases were selected on an evidence-based analysis of respective clinical trials. Subsequent to narrative choices by two metabolic bone disease specialists (SG and CR), calculation of future fracture risk and selection of potential alternative therapeutic regimens were reviewed and critiqued by an epidemiologist (DB). Results: A narrative about each case and possible management choices for each of the five cases are presented with references to justify selection of the various therapeutic options. Alternatives are considered and discussed based on literature and references through July 2003. The disposition of the individual patient is noted at the end of each case. Conclusions: A case-based approach to the management of osteoporosis provides a useful interface between guidelines, evidence-based meta-analyses, and clinical practice dilemmas. [source] Osteoclastogenesis, Bone Resorption, and Osteoclast-Based TherapeuticsJOURNAL OF BONE AND MINERAL RESEARCH, Issue 4 2003Mone Zaidi Abstract Over the past decade, advances in molecular tools, stem cell differentiation, osteoclast and osteoblast signaling mechanisms, and genetically manipulated mice models have resulted in major breakthroughs in understanding osteoclast biology. This review focuses on key advances in our understanding of molecular mechanisms underlying the formation, function, and survival of osteoclasts. These include key signals mediating osteoclast differentiation, including PU.1, RANK, CSF-1/c-fms, and src, and key specializations of the osteoclast including HCl secretion driven by H+ -ATPase and the secretion of collagenolytic enzymes including cathepsin K and matrix metalloproteinases (MMPs). These pathways and highly expressed proteins provide targets for specific therapies to modify bone degradation. The main outstanding issues, basic and translational, will be considered in relation to the osteoclast as a target for antiresorptive therapies. [source] Potential of umbilical cord blood cells for brain repairJOURNAL OF NEUROCHEMISTRY, Issue 2002P. R. Sanberg Our laboratory is characterizing the mononuclear cells from human umbilical cord blood (HUCB) for possible therapeutic value. Studies on HUCB cells demonstrated their ability to respond to growth factors by increased expression of neural markers and down regulation of several genes associated with development of blood lines. HUCB cells were also transplanted into the subventricular zone of the developing rat brain. It was found that some of the HUCB cells responded to external factors and were able to adopt neural fates similar to endogenous stem cells. We also tested whether intravenously infused HUCB cells enter brain, survive, differentiate and improve neurological functional recovery after stroke or traumatic brain injury (TBI) in rats. HUCB cells were injected into the tail vein at least 24 h after stroke or TBI. Behavioral impairments were significantly improved as early as 14 days in both TBI and stroke animals, compared to controls. Injected cells entered brain and migrated into the parenchyma of the injured brain. Some of these expressed neuronal, astrocytic, or endothelial markers. Our data suggest that intravenous administration of HUCB cells can provide neural stem cells, and may be a useful treatment for brain repair. Acknowledgements:, Supported by Saneron CCEL Therapeutics, Inc. and a FL Hi-Tech Corridor Grant. [source] Exploration of developmental approaches to companion animal antimicrobials: providing for the unmet therapeutic needs of dogs and catsJOURNAL OF VETERINARY PHARMACOLOGY & THERAPEUTICS, Issue 2 2010AAVPT, White Paper Committee Committee members:, Workshop AAVPT Workshop White Paper Committee. Exploration of developmental approaches to companion animal antimicrobials: providing for the unmet therapeutic needs of dogs and cats. J. vet. Pharmacol. Therap.33, 196,201. The American Academy of Veterinary Pharmacology and Therapeutics (AAVPT) and the United States Pharmacopeia (USP) co-sponsored a workshop to explore approaches for developing companion animal antimicrobials. This workshop was developed in response to the shortage of antimicrobials labeled for dogs and cats, as there is a shortage of approved antimicrobials for the range of infectious diseases commonly treated in small animal practice. The objective of the workshop was to identify alternative approaches to data development to support new indications consistent with the unmet therapeutic needs of dogs and cats. The indications for currently approved antimicrobials do not reflect the broader range of infectious diseases that are commonly diagnosed and treated by the veterinarian. Therefore, the labels for these approved antimicrobials provide limited information to the veterinarian for appropriate therapeutic decision-making beyond the few indications listed. Industry, veterinary practice, and regulatory challenges to the development of new antimicrobial indications were discussed. The workshop resulted in short- and long-term recommendations. Short-term recommendations focus on the use of additional data considerations for product labeling. Long-term recommendations center on legislative or regulatory legal initiatives. The workshop recommendations will need collaboration from industry, academia, and regulatory authorities and a legal shift in the drug approval and availability processes. [source] Alimentary Pharmacology & TherapeuticsALIMENTARY PHARMACOLOGY & THERAPEUTICS, Issue 1 2008Professor R.E. Pounder No abstract is available for this article. [source] Critical Therapeutics: Cultural Politics and Clinical Reality in Two Eating Disorder Treatment CentersMEDICAL ANTHROPOLOGY QUARTERLY, Issue 4 2007Rebecca J. Lester Recent studies suggest that eating disorders are increasing in Mexico and that this seems to correspond with Mexico's push to modernization. In this respect, Mexico exemplifies the acculturation hypothesis of eating disorders, namely, that anorexia and bulimia are culture-bound syndromes tied to postindustrial capitalist development and neoliberalist values, and that their appearance elsewhere is indicative of acculturation to those values. Available evidence for this claim, however, is often problematic. On the basis of five years of comparative fieldwork in eating disorder clinics in Mexico City and a small Midwestern city in the United States, I reframe this as an ethnographic question by examining how specific clinical practices at each site entangle global diagnostic categories with local social realities in ways that problematize existing epistemologies about culture and illness. In this regard, debates about acculturation and the global rise of eating disorders foreground issues of central epistemological and practical importance to contemporary medical anthropology more generally. [source] Benefit assessment of therapeutic products: the Centers for Education and Research on Therapeutics,PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, Issue 1 2007Robert M. Califf MD Abstract The ability to manage risk depends critically on an understanding of the degree to which a known risk is balanced by the probability of a clinical benefit. Despite the massive emphasis on risk and risk management in the past few years and the long-term focus on defining benefit in the regulatory system, considerable uncertainty remains about the methods of defining benefit and how to operationalize this knowledge. In this ,think tank,' part of a larger series on risk management, issues were divided into those that can be identified before a study is initiated, those that commonly arise after a study is completed, biomarkers and surrogates, use of benefit findings in defining quality and performance indicators, implementation of findings into health systems and formularies, and methods of comparative trials. Key categories for the establishment of a research agenda to fill in gaps in our understanding of assessing benefit were developed by the group. Copyright © 2006 John Wiley & Sons, Ltd. [source] Use of prescription medications with a potential for fetal harm among pregnant women,PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, Issue 8 2006Susan E. Andrade ScD Abstract Purpose To estimate the prevalence of use of prescription drugs with a potential for fetal harm among pregnant women in the United States. Methods A retrospective study was conducted using the automated databases of eight health maintenance organizations involved in the HMO Research Network Center for Education and Research on Therapeutics (CERT). Women who delivered an infant from January 1996 to December 2000 were identified. The frequency of use of prescription drugs with a potential for fetal harm was based upon the expert review of a clinical teratologist and the U.S. Food and Drug Administration (FDA) risk classification system, assuming a gestational duration of 270 days. Results Among the 114,165 women with no documentation of a diagnosis suggesting potential pre-term birth or dispensing of ovulation stimulants in the 270 days before delivery, 1305 (1.1%) received a teratogenic drug during the 270 days before delivery, based upon the expert review of a clinical teratologist. A larger proportion of women received U.S. FDA category D or X drugs (5.8%; N,=,6600). However, the general patterns of use were similar, with higher use in early pregnancy compared to later trimesters. The proportion of women dispensed a teratogen during pregnancy was substantially higher among women who received a teratogen in the 90 days before pregnancy compared to women who did not (adjusted RR,=,38.9, 95%CI, 33.5, 45.3). Conclusions Our results suggest that further efforts directed at physicians to counsel women or at the women themselves about the potential risks of particular medications appear warranted. Copyright © 2006 John Wiley & Sons, Ltd. [source] Evaluation of gestational age and admission date assumptions used to determine prenatal drug exposure from administrative data,PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, Issue 12 2005Marsha A. Raebel PharmD Abstract Objective Our aim was to evaluate the 270-day gestational age and delivery date assumptions used in an administrative dataset study assessing prenatal drug exposure compared to information contained in a birth registry. Study Design and Setting Kaiser Permanente Colorado (KPCO), a member of the Health Maintenance Organization (HMO) Research Network Center for Education and Research in Therapeutics (CERTs), previously participated in a CERTs study that used claims data to assess prenatal drug exposure. In the current study, gestational age and deliveries information from the CERTs study dataset, the Prescribing Safely during Pregnancy Dataset (PSDPD), was compared to information in the KPCO Birth Registry. Sensitivity and positive predictive value (PPV) of the claims data for deliveries were assessed. The effect of gestational age and delivery date assumptions on classification of prenatal drug exposure was evaluated. Results The mean gestational age in the Birth Registry was 273 (median,=,275) days. Sensitivity of claims data at identifying deliveries was 97.6%, PPV was 98.2%. Of deliveries identified in only one dataset, 45% were related to the gestational age assumption and 36% were due to claims data issues. The effect on estimates of prevalence of prescribing during pregnancy was an absolute change of 1% or less for all drug exposure categories. For Category X, drug exposures during the first trimester, the relative change in prescribing prevalence was 13.7% (p,=,0.014). Conclusion Administrative databases can be useful for assessing prenatal drug exposure, but gestational age assumptions can result in a small proportion of misclassification. Copyright © 2005 John Wiley & Sons, Ltd. [source] The importance of news media in pharmaceutical risk communication: proceedings of a workshop,,§PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, Issue 5 2005Felicia E. Mebane PhD Abstract In response to mass media's role in the national and global system of pharmaceutical risk communication, the Centers for Education and Research on Therapeutics (CERTs) convened a ,think tank' session on the ,Importance of Media in Pharmaceutical Risk Communication'. Prominent journalists and experts from the pharmaceutical industry, academia, medical practice and government were invited to consider the benefits and challenges of improving the way we communicate the benefits and risks of therapeutics via mass media, especially news media. Workshop discussions revealed a paucity of systematic research directed towards understanding how and why news media report on therapeutic risk, the impact of this coverage and how coverage can be improved. Consequently, participants produced a research agenda capturing the key aspects of the flow of information around this topic, including the meaning of risk, how news audiences process and use therapeutic risk information in the news, how and why news organizations report on therapeutic risk, and the role and impact of the pharmaceutical industry, government officials and academic researchers as sources of therapeutic risk information. The workshop ended with a discussion on action items addressing what news professionals, representatives of regulatory agencies and the medical products industry, and academic researchers can and should do to enable news media to effectively report therapeutic risk information. In sum, this proceedings report provides an outline for developing mass media risk communication research, influencing the practices of journalists and expert sources and ultimately, improving the quality of the public's life. Copyright © 2004 John Wiley & Sons, Ltd. [source] Risk assessment of drugs, biologics and therapeutic devices: present and future issues,PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, Issue 8 2003B. L. Strom Abstract Purpose The current US system for detecting adverse effects of therapeutics (drugs, devices and biological products) is suboptimal. This report presents the results of an expert workshop on assessing therapeutic risks. This is the second of five workshops coordinated by the Centers for Education and Research on Therapeutics (CERTs) to address the management of therapeutic risks relative to potential benefits. Methods The workshop included academic, industry, government and constituency-based leaders. The focus was on the postapproval phase and procedures in the US, but relevant international issues and attendees were included. Results Substantial deficiencies in the current US system for risk assessment were delineated. Improving the system will involve research into methods to improve risk assessment, enhancement and consolidation of data-handling systems, education of healthcare workers, allocation of financial resources and building of constituencies. Conclusions We need leadership on multiple levels for global coordination of risk assessment. We can then begin to fill gaps and produce benefits for industry, health authorities, government agencies, healthcare providers, and most important, the public. Copyright © 2003 John Wiley & Sons, Ltd. [source] Improving communication of drug risks to prevent patient injury: proceedings of a workshopPHARMACOEPIDEMIOLOGY AND DRUG SAFETY, Issue 3 2003William H. Campbell Abstract Purpose The Centers for Education & Research on Therapeutics (CERTs) is conducting a series of workshops on managing the risks of therapeutics, with the ultimate goal to develop an agenda for research and education about risk and its management. This paper presents the results of the first workshop in the series, a 2-day meeting focused on communication of drug risks to healthcare professionals and patients. Methods The 50 workshop participants represented the medical-products industry, academia, consumer groups, regulatory bodies and the media. Together, they sought to identify and understand barriers to successful risk communication, to identify tools or methods that could improve risk communication, and to develop research and education agendas that would lead to better risk communication in the future. Results Limitations of current methods of risk communication were identified, and research and education agendas were proposed to clarify and resolve these issues. Conclusion Common themes for potential solutions include enhanced education of healthcare providers, increased motivation of patients and families, use of creative communication technologies, and better organization of and access to medical records and information. Copyright © 2002 John Wiley & Sons, Ltd. [source] Databases for outcomes research: what has 10 years of experience taught us?PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, Issue 5 2001Lynn Bosco MD Abstract This paper describes how the mission of the Agency for Healthcare Research and Quality (AHRQ) is being executed through the many programs that it has developed and implemented. The Evidence-based Practice Center program was developed to provide systematic reviews on common and expensive conditions and health technologies and to ensure that this information is used to improve health care outcomes and costs. The National Guidelines Clearinghouse provides an internet-based source of clinical practice guidelines that are produced by clinical specialty organizations for the primary purpose of improving health care delivery and outcomes. Relevant to this symposium on databases, AHRQ has supported the development of databases to track hospital utilization on a state-by-state basis. The Healthcare Cost and Utilization Project (HCUP) allows comparisons between states and within regions of individual states. New initiatives have been launched to evaluate interventions across systems rather than focusing on the individual patient (Translating Research into Practice,TRIP). The Centers for Education and Research on Therapeutics (CERTs) program was developed to conduct real world evaluations to better understand the benefits and risks of single and combined therapy. Both programs further the mission of the AHRQ to improve the outcomes and quality of health care, with additional focus on the cost-effectiveness, patient safety, and increasing access to care for all. Information on programs developed by the AHRQ is available in more detail at the Agency Web site http://www.ahrq.gov. Copyright © 2001 John Wiley & Sons, Ltd. [source] Patents and Innovation in Cancer Therapeutics: Lessons from CellProTHE MILBANK QUARTERLY, Issue 4 2002Avital Bar-Shalom How scientific knowledge is translated into diagnostic and therapeutic tools is important to patients with dread diseases as well as to regulators and policymakers. Patents play a crucial role in that process. Indeed, concern that the fruits of federally funded research would languish without commercial application led to the passage of the Bayh-Dole Act (PL 96-517), which reinforced incentives to patent the results of inventions arising from federally funded research (Eisenberg 1996). Subsequently, rates of patenting among U.S. academic institutions have increased (Henderson, Jaffe, and Trajtenberg 1988). A recent survey by the Association of University Technology Managers counted 20,968 licenses and options from 175 academic institutions and 6,375 patent applications filed in fiscal year 2000 (Pressman 2002). Analysis suggests that the number of academic patents was already rising when the Bayh-Dole Act was passed in 1980 (Mowery et al. 2001), but it is clear that the act reinforced the patenting norm in research universities and mandated a technology transfer infrastructure at those universities that had not yet established a technology licensing office. This article discusses the interaction between intellectual property and cancer treatment. CellPro developed a stem cell separation technology based on research at the Fred Hutchinson Cancer Center. A patent with broad claims to bone marrow stem cell antibodies had been awarded to Johns Hopkins University and licensed to Baxter Healthcare under the 1980 Bayh-Dole Act to promote commercial use of inventions from federally funded research. CellPro got FDA approval more than two years before Baxter but lost patent infringement litigation. NIH elected not to compel Hopkins to license its patents to CellPro. CellPro went out of business, selling its technology to its competitor. Decisions at both firms and university licensing offices, and policies at the Patent and Trademark Office, NIH, and the courts influenced the outcome. [source] Drug-Free Macromolecular Therapeutics: Induction of Apoptosis by Coiled-Coil-Mediated Cross-Linking of Antigens on the Cell Surface,ANGEWANDTE CHEMIE, Issue 8 2010Kuangshi Wu Peptide verbinden: Die Bildung von Heterodimeren mit Doppelwendelstrukturen aus komplementären Zufallsknäuel-Peptiden, von denen eines an ein Antikörper-Fragment (grau; rotes Peptid) und das andere an ein Copolymer (schwarz; grünes Peptid) gekuppelt ist, vernetzt CD20-Zielantigene (orange) auf Raji-B-Zellen und löst dadurch eine Apoptose aus (siehe Schema). [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] Protein Kinase C Activators as Synaptogenic and Memory TherapeuticsARCHIV DER PHARMAZIE, Issue 12 2009Miao-Kun Sun Abstract The last decade has witnessed a rapid progress in understanding of the molecular cascades that may underlie memory and memory disorders. Among the critical players, activity of protein kinase C (PKC) isoforms is essential for many types of learning and memory and their dysfunction, and is critical in memory disorders. PKC inhibition and functional deficits lead to an impairment of various types of learning and memory, consistent with the observations that neurotoxic amyloid inhibits PKC activity and that transgenic animal models with PKC, deficit exhibit impaired capacity in cognition. In addition, PKC isozymes play a regulatory role in amyloid production and accumulation. Restoration of the impaired PKC signal pathway pharmacologically results in an enhanced memory capacity and synaptic remodeling / repair and synaptogenesis, and, therefore, represents a potentially important strategy for the treatment of memory disorders, including Alzheimer's dementia. The PKC activators, especially those that are isozyme-specific, are a new class of drug candidates that may be developed as future memory therapeutics. [source] Synthesis of Monomeric and Dimeric Acridine Compounds as Potential Therapeutics in Alzheimer and Prion DiseasesARCHIV DER PHARMAZIE, Issue 12 2009René Csuk Abstract Starting from substituted 9-chloroacridines, a series of quinacrine and spacered dimeric acridine compounds was prepared. Their ability to interrupt the protein association of prion- and Alzheimer-specific proteins and Ab peptides was explored using a fast screening system based on FACS analysis. The bis-acridines displayed a higher activity than the corresponding monomers. Among these derivatives, best results were obtained with the 2,4-dimethoxy-6-nitro compound 7h for A,-peptides and the 2-methoxy-6-nitro compound 7f for PrP. [source] Do the learning needs of rural and urban general practitioners differ?AUSTRALIAN JOURNAL OF RURAL HEALTH, Issue 6 2005James A. Allan Abstract Introduction:,The challenges of rural general practice have given rise to a separate rural training stream and a separate rural professional body. The differences are characterised by the nature of the work undertaken by rural GPs and reflected in the continuing medical education topic choices made when surveyed. Methods:,In 2001 a survey was designed and distributed by the Royal Australian College of General Practitioners and Divisions of General Practice in South Australia and Northern Territory. The survey utilised a list of 104 topics. The topic choices of rural and urban GPs were compared. Results:,The survey was distributed to approximately 1762 GPs and yielded 578 responses (33%). Rural GPs were more likely to select the following topics: Anaesthetics, Aboriginal Torres Strait Islander health, Population Health, Renal medicine, Cardiology, Teaching skills, Obstetrics, Neonates, Arrhythmias, Fracture management, Tropical medicine and Therapeutics. Urban GPs were more likely to select Menopause, Travel medicine and Palliative care (P < 0.05). Discussion:,Many of the areas of difference reflected aspects of rural general practice. There were also many similarities in topic choices between these two groups. [source] Educating European (Junior) Doctors for Safe PrescribingBASIC AND CLINICAL PHARMACOLOGY & TOXICOLOGY, Issue 6 2007Simon R. J. Maxwell Junior doctors who have recently graduated are responsible for much of the prescribing that takes place in hospitals and are implicated in many of the adverse medication events. Analysis of such events suggests that lack of knowledge and training underlies many of them and it has been shown that dedicated training can increase prescribing performance. In the context of these problems, it is a matter of increasing concern that recent changes to undergraduate medical education may have reduced exposure to clinical pharmacology, a discipline dedicated to optimal practice in relation to medicines. For this reason, the European Association of Clinical Pharmacology and Therapeutics (EACPT) and British Pharmacological Society (BPS) jointly organized a meeting to explore (i) the state of undergraduate education in clinical pharmacology in Europe, (ii) the knowledge and competencies in relation to medicines that should be expected of a new graduate, (iii) assessments that might demonstrate that this minimum standard had been reached, (iv) a curriculum that might help medical students to achieve this standard and (v) how competence can be developed in the postgraduate phase. It was agreed that the lack of exposure to clinical pharmacology is a cause for concern at a time when the challenges facing junior prescribers have never been greater. The potential for undertaking further research was discussed. [source] The European Association for Clinical Pharmacology and Therapeutics and the Journal Basic & Clinical Pharmacology & ToxicologyBASIC AND CLINICAL PHARMACOLOGY & TOXICOLOGY, Issue 1 2007Michael Orme Chairman of EACPT 200 No abstract is available for this article. [source] Molecular Therapeutics: 21st century medicine by Pamela Greenwell and Michelle McCulleyBIOCHEMISTRY AND MOLECULAR BIOLOGY EDUCATION, Issue 6 2008Robert H. Glew No abstract is available for this article. [source] Prediction and Reverse Prediction in Therapeutics and ToxicologyBRITISH JOURNAL OF CLINICAL PHARMACOLOGY, Issue 4 2008J. M. Ritter Editor-in-Chief British Journal of Clinical Pharmacology No abstract is available for this article. [source] Oral retinoic acid metabolism blocking agent RambazoleTM for plaque psoriasis: an immunohistochemical studyBRITISH JOURNAL OF DERMATOLOGY, Issue 2 2007H.J. Bovenschen Summary Background, The novel systemic all- trans retinoic acid metabolism blocking agent (RAMBA) R115866 (RambazoleTM; Barrier Therapeutics, Geel, Belgium; further referred to as rambazole) increases intracellular levels of endogenous all- trans retinoic acid (RA). Well-known effects of RA are normalization of aberrant epithelial growth and differentiation. Hence, rambazole might be beneficial in the treatment of plaque psoriasis. Objectives, The dynamics of epidermal proliferation, keratinization, lesional T-cell subsets and cells expressing natural killer (NK)-receptors in plaque psoriasis were assessed during treatment with rambazole, as part of a phase IIa open-label clinical trial. Methods, Six patients were treated with rambazole, 1 mg, once daily, for 8 weeks. At weeks 0, 2 and 8, psoriatic plaque severity scores (SUM) and biopsies from a target lesion were assessed. Epidermal proliferation (Ki67), keratinization markers (K10, K13, K19), T-cell subsets (CD3, CD4+, CD8+, CD45RO+, CD45RA+, CD2+, CD25+, GITR+) and cells expressing NK-receptors (CD94, CD161) were immunohistochemically stained and quantified with image analysis. Results, At week 2 the mean SUM-score was virtually equal to baseline, which was accompanied immunohistochemically by equal epidermal hyperproliferation, a nonsignificant decrease in K10 positive epidermis and, overall, a nonsignificant increase in immunocyte subsets. At week 8, in contrast, plaque severity was reduced by 34% from baseline (P < 0·05). Improvements were also detected for epidermal proliferation (,63%; P < 0·01) and K10 expression (+29%; P < 0·01), compared with baseline. No induction of retinoid-specific keratinization (K13, K19) was observed. A nonsignificant reduction of all pathogenic T-cell subsets and cells expressing NK-receptors was observed at week 8 of treatment (P > 0·05). Conclusions, Clinical efficacy of rambazole is primarily the result of restoring proliferation (Ki67) and differentiation (K10) of epidermal keratinocytes. Secondly, relevant T-cell subsets and cells expressing NK-receptors showed nonsignificant reductions after 8 weeks of treatment with rambazole. [source] | ||||||||||||||||||||||||||||||||||||||||