Clinical studies of experimental vaccines.

PURPOSE OF REVIEW: The scope of this review is to provide the current status of HIV vaccine clinical development. A series of issues regarding the type of immune response stimulated by the candidate vaccines in the pipeline, the advances in the immune correlates of protection, the need for an effective decision-making process for selection of candidate vaccines into further clinical development and the rationale for clinical trials will also be discussed. RECENT FINDINGS: Efforts in the development of HIV vaccines inducing broad neutralizing antibodies have failed so far. The current pipeline is predominantly composed of candidate vaccines designed to induce cellular immunity and particularly T-cell response. For these reasons, these candidate vaccines have been termed 'T-cell vaccines'. A large number of candidate vaccines or vaccine combinations have entered phase I-II clinical trials in 2005. Furthermore, an adenovirus vector-based vaccine has entered proof-of-concept efficacy trial and a canarypox vector in combination with a protein-based vaccine is currently being evaluated in phase III clinical trials. T-cell vaccines have been shown to be safe and the most recent generation of these vaccines also has substantial immunogenicity. SUMMARY: Only clinical trials can provide the definitive answer to immune correlates of protection and vaccine efficacy.

Waste management policies for industrial symbiosis development: case studies in European countries

Industrial symbiosis (IS) emerged as a self-organizing business strategy among firms that are willing to cooperate to improve their economic and environmental performance. The adoption of such cooperative strategies relates to increasing costs of waste management, most of which are driven by policy and legislative requirements. Development of IS depends on an enabling context of social, informational, technological, economical and political factors. The power to influence this context varies among the agents involved such as the government, businesses or coordinating entities. Governmental intervention, as manifested through policies, could influence a wider range of factors; and we believe this is an area which is under-researched. This paper aims to critically appraise the waste policy interventions from supra-national to sub-national levels of government. A case study methodology has been applied to four European countries i.e. Denmark, the UK, Portugal and Switzerland, in which IS emerged or is being fostered. The findings suggest that there are commonalities in policy instruments that may have led to an IS enabling context. The paper concludes with lessons learnt and recommendations on shaping the policy context for IS development.

Mutation screening of the urocortin gene: identification of new single nucleotide polymorphisms and association studies with obesity in French Caucasians.

A linkage between obesity-related phenotypes and the 2p21-23 locus has been reported previously. The urocortin (UCN) gene resides at this interval, and its protein decreases appetite behavior, suggesting that UCN may be a candidate gene for susceptibility to obesity. We localized the UCN gene by radiation hybrid mapping, and the surrounding markers were genotyped in a collection of French families. Evidence for linkage was shown between the marker D2S165 and leptin levels (LOD score, 1.34; P = 0.006) and between D2S2247 and the z-score of body mass index (LOD score, 1.829; P = 0.0019). The gene was screened for SNPs in 96 obese patients. Four new variants were established. Two single nucleotide polymorphisms were located in the promoter (-535 A-->G, -286 G-->A), one in intron 1 (+31 C-->G), and one in the 3'-untranslated region (+34 C-->T). Association studies in cohorts of 722 unrelated obese and 381 control subjects and transmission disequilibrium tests, performed for the two frequent promoter polymorphisms, in 120 families (894 individuals) showed that no association was present between these variants and obesity, obesity-related phenotypes, and diabetes. Thus, our analyses of the genetic variations of the UCN gene suggest that, at least in French Caucasians, they do not represent a major cause of obesity.

Body mass index and risk of head and neck cancer in a pooled analysis of case-control studies in the International Head and Neck Cancer Epidemiology (INHANCE) Consortium.

BACKGROUND: Head and neck cancer (HNC) risk is elevated among lean people and reduced among overweight or obese people in some studies; however, it is unknown whether these associations differ for certain subgroups or are influenced by residual confounding from the effects of alcohol and tobacco use or by other sources of biases. METHODS: We pooled data from 17 case-control studies including 12 716 cases and the 17 438 controls. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated for associations between body mass index (BMI) at different ages and HNC risk, adjusted for age, sex, centre, race, education, tobacco smoking and alcohol consumption. RESULTS: Adjusted ORs (95% CIs) were elevated for people with BMI at reference (date of diagnosis for cases and date of selection for controls) 25.0-30.0 kg/m(2) (0.52, 0.44-0.60) and BMI >/=30 kg/m(2) (0.43, 0.33-0.57), compared with BMI >18.5-25.0 kg/m(2). These associations did not differ by age, sex, tumour site or control source. Although the increased risk among people with BMI 25 kg/m(2) was present only in smokers and drinkers. CONCLUSIONS: In our large pooled analysis, leanness was associated with increased HNC risk regardless of smoking and drinking status, although reverse causality cannot be excluded. The reduced risk among overweight or obese people may indicate body size is a modifier of the risk associated with smoking and drinking. Further clarification may be provided by analyses of prospective cohort and mechanistic studies.

Novel method to estimate the phenotypic variation explained by genome-wide association studies reveals large fraction of the missing heritability.

Genome-wide association studies (GWAS) are conducted with the promise to discover novel genetic variants associated with diverse traits. For most traits, associated markers individually explain just a modest fraction of the phenotypic variation, but their number can well be in the hundreds. We developed a maximum likelihood method that allows us to infer the distribution of associated variants even when many of them were missed by chance. Compared to previous approaches, the novelty of our method is that it (a) does not require having an independent (unbiased) estimate of the effect sizes; (b) makes use of the complete distribution of P-values while allowing for the false discovery rate; (c) takes into account allelic heterogeneity and the SNP pruning strategy. We applied our method to the latest GWAS meta-analysis results of the GIANT consortium. It revealed that while the explained variance of genome-wide (GW) significant SNPs is around 1% for waist-hip ratio (WHR), the observed P-values provide evidence for the existence of variants explaining 10% (CI=[8.5-11.5%]) of the phenotypic variance in total. Similarly, the total explained variance likely to exist for height is estimated to be 29% (CI=[28-30%]), three times higher than what the observed GW significant SNPs give rise to. This methodology also enables us to predict the benefit of future GWA studies that aim to reveal more associated genetic markers via increased sample size.

Studies of the association of the A, B and Lewis Blood group antigens with carcinoembryonic antigen (CEA).

Carcinoembryonic antigen (CEA) was purified from primary tumour or from hepatic metastases obtained from ten cases of carcinoma of the colon. In nine cases the blood group antigens A, B, Lea or Leb were detected in CEA preparations by the binding of 125I-labelled CEA by blood group antibodies. The extent of binding appeared to preclude simple contamination of CEA preparations by blood group glycoprotein. In all cases the blood group antigens detected were consistent with the patients' known blood groups. Blood group I and i activities were not detected. It is concluded that the determinants of A, B and Lewis antigens and of CEA share the same glycoprotein carrier molecules.

Diagnostic interview for genetic studies (DIGS): inter-rater and test-retest reliability of alcohol and drug diagnoses

The semi-structured diagnostic interview for genetic studies (DIGS) was developed to assess major mood and psychotic disorders and their spectrum manifestations in genetic studies. Our research group developed a French version of the DIGS and tested its inter-rater and test-retest reliability in psychiatric patients. In this article, we present estimates of the reliability of substance use and antisocial personality disorders. High kappa coefficients for inter-rater reliability were found for drug and alcohol as well as antisocial personality diagnoses and slightly lower kappas for test-retest reliability. Combined with evidence of the reliability of major mood and psychotic disorders, these findings support the suitability of the DIGS for studies of familial aggregation and comorbidity of psychiatric disorders including substance use and antisocial personality disorders.

Do Objective Measures of Blood Alcohol Concentrations Make More Sense than Self-reports in Emergency Department Studies?

Purpose: Concerns about self-reports have led to calls for objective measures of blood alcohol concentration (BAC). The present study compared objective measures with self-reports. Methods: BAC from breath or blood samples were obtained from 272 randomly sampled injured patients who were admitted to a Swiss emergency department (ED). Self-reports were compared a) between those providing and refusing a BAC test, and b) to estimated peak BAC (EPBAC) values based on BACs using the Widmark formula. Results: Those providing BACs were significantly (P < 0.05) younger, more often male, and less often reported alcohol consumption before injury, but consumed higher quantities when drinking. Eighty-eight percent of those with BAC measures gave consistent reports (positive or negative). Significantly more patients reported consumption with negative BAC measures (N = 29) than vice versa (N = 3). Duration of consumption and times between injury and BAC measurement predicted EPBAC better than did the objective BAC measure. Conclusions: There is little evidence that patients who provide objective BAC measures deliberately conceal consumption. ED studies must rely on self-reports, eg, take the time period between injury and ED admission into account. Clearly, objective measures are of clinical relevance, eg, to provide optimal treatment in the ED. However, they may be less relevant to establishing effects in an epidemiologic sense, such as estimating risk relationships. In this respect, efforts to increase the validity and reliability of self-reports should be preferred over the collection of additional objective measures.

Studies toward new anti-cancer strategies based on alpha-mannosidase inhibition.

Changes in the glycosylation pattern of cellular glycoproteins constitute a hallmark in human cancer and influence tumor progression, suggesting that inhibitors of selected glycosidases may control cancer progression. Following the studies on swainsonine, a natural inhibitor of Golgi alpha-mannosidase II, which highlighted the inhibition of cellular mannosidases as a potential innovative approach for the treatment of cancer, several dihydroxylated pyrrolidines and analogues were developed as new potent inhibitors of alpha-mannosidases II able to induce antiproliferative effects in human cancer cells.

Computational analysis of the genetic and environmental contributions to disease-related human phenotypes: From predicting adverse lipid response of HIV patients receiving antiretroviral therapy to genome-wide association studies of cardiovascular and lipid related disorders

Genetic variants influence the risk to develop certain diseases or give rise to differences in drug response. Recent progresses in cost-effective, high-throughput genome-wide techniques, such as microarrays measuring Single Nucleotide Polymorphisms (SNPs), have facilitated genotyping of large clinical and population cohorts. Combining the massive genotypic data with measurements of phenotypic traits allows for the determination of genetic differences that explain, at least in part, the phenotypic variations within a population. So far, models combining the most significant variants can only explain a small fraction of the variance, indicating the limitations of current models. In particular, researchers have only begun to address the possibility of interactions between genotypes and the environment. Elucidating the contributions of such interactions is a difficult task because of the large number of genetic as well as possible environmental factors.In this thesis, I worked on several projects within this context. My first and main project was the identification of possible SNP-environment interactions, where the phenotypes were serum lipid levels of patients from the Swiss HIV Cohort Study (SHCS) treated with antiretroviral therapy. Here the genotypes consisted of a limited set of SNPs in candidate genes relevant for lipid transport and metabolism. The environmental variables were the specific combinations of drugs given to each patient over the treatment period. My work explored bioinformatic and statistical approaches to relate patients' lipid responses to these SNPs, drugs and, importantly, their interactions. The goal of this project was to improve our understanding and to explore the possibility of predicting dyslipidemia, a well-known adverse drug reaction of antiretroviral therapy. Specifically, I quantified how much of the variance in lipid profiles could be explained by the host genetic variants, the administered drugs and SNP-drug interactions and assessed the predictive power of these features on lipid responses. Using cross-validation stratified by patients, we could not validate our hypothesis that models that select a subset of SNP-drug interactions in a principled way have better predictive power than the control models using "random" subsets. Nevertheless, all models tested containing SNP and/or drug terms, exhibited significant predictive power (as compared to a random predictor) and explained a sizable proportion of variance, in the patient stratified cross-validation context. Importantly, the model containing stepwise selected SNP terms showed higher capacity to predict triglyceride levels than a model containing randomly selected SNPs. Dyslipidemia is a complex trait for which many factors remain to be discovered, thus missing from the data, and possibly explaining the limitations of our analysis. In particular, the interactions of drugs with SNPs selected from the set of candidate genes likely have small effect sizes which we were unable to detect in a sample of the present size (<800 patients).In the second part of my thesis, I performed genome-wide association studies within the Cohorte Lausannoise (CoLaus). I have been involved in several international projects to identify SNPs that are associated with various traits, such as serum calcium, body mass index, two-hour glucose levels, as well as metabolic syndrome and its components. These phenotypes are all related to major human health issues, such as cardiovascular disease. I applied statistical methods to detect new variants associated with these phenotypes, contributing to the identification of new genetic loci that may lead to new insights into the genetic basis of these traits. This kind of research will lead to a better understanding of the mechanisms underlying these pathologies, a better evaluation of disease risk, the identification of new therapeutic leads and may ultimately lead to the realization of "personalized" medicine.