Body composition using bio-impedance analysis in pediatric patients with inflammatory bowel disease. Corcordance with dual energy X-ray absorptiometry and comparison with healthy controls

Introduction: Growth is a central process in paediatrics. Weight and height evaluation are therefore routine exams for every child but in some situation, particularly inflammatory bowel disease (IBD), a wider evaluation of nutritional status needs to be performed. Objectives: To assess the accuracy of bio-impedance analysis (BIA) compared to the gold standard dual energy X-ray absorptiometry (DEXA) in estimating percentage body fat (fat mass; FM) and lean body mass (fat free mass; FFM) in children with inflammatory bowel disease (IBD). To compare FM and FFM levels between patients with IBD and healthy controls. Methods: Twenty-nine healthy controls (12 females; mean age: 12.7 ± 1.9 years) and 21 patients (11 females; 14.3 ± 1.3 years) were recruited from August 2011 to October 2012 at our institution. BIA was performed in all children and DEXA in patients only. Concordance between BIA and DEXA was assessed using Lin's concordance correlation and the Bland-Altman method. Between-group comparisons were made using analysis of variance adjusting for age. Results: BIA-derived FM% showed a good concordance with DEXA-derived values, while BIA-derived FFM% tended to be slightly higher than DEXA-derived values (table). No differences were found between patients and controls regarding body mass index (mean ± SD: 19.3 ± 3.3 vs. 20.1 ± 2.8 kg/m2, respectively; age-adjusted P = 0.08) and FM% (boys: 25.3 ± 10.2 vs. 22.6 ± 7.1%, for patients and controls, respectively; P = 0.20; girls: 28.2 ± 5.7 vs. 26.4 ± 7.7%; P = 0.91). Also, no differences were found regarding FFM% in boys (74.9 ± 10.2 vs. 77.4 ± 7.1%; P = 0.22) and girls (71.8 ± 5.6 vs. 73.5 ± 7.7%; P = 0.85). Conclusion: BIA adequately assesses body composition (FM%) in children with IBD and could advantageously replace DEXA, which is more expensive and less available. No differences in body composition were found between children with IBD and healthy controls.

The evolution and consequences of sex-specific reproductive variance.

Natural selection favors alleles that increase the number of offspring produced by their carriers. But in a world that is inherently uncertain within generations, selection also favors alleles that reduce the variance in the number of offspring produced. If previous studies have established this principle, they have largely ignored fundamental aspects of sexual reproduction and therefore how selection on sex-specific reproductive variance operates. To study the evolution and consequences of sex-specific reproductive variance, we present a population-genetic model of phenotypic evolution in a dioecious population that incorporates previously neglected components of reproductive variance. First, we derive the probability of fixation for mutations that affect male and/or female reproductive phenotypes under sex-specific selection. We find that even in the simplest scenarios, the direction of selection is altered when reproductive variance is taken into account. In particular, previously unaccounted for covariances between the reproductive outputs of different individuals are expected to play a significant role in determining the direction of selection. Then, the probability of fixation is used to develop a stochastic model of joint male and female phenotypic evolution. We find that sex-specific reproductive variance can be responsible for changes in the course of long-term evolution. Finally, the model is applied to an example of parental-care evolution. Overall, our model allows for the evolutionary analysis of social traits in finite and dioecious populations, where interactions can occur within and between sexes under a realistic scenario of reproduction.

Diallel analysis for grain yield and mineral absorption rate of soybeans grown in acid brazilian savannah soil

High available aluminium and low levels of calcium below the ploughed zone of the soil are limiting factors for agricultural sustainability in the Brazilian Cerrados (Savannahs). The mineral stresses compound with dry spells effect by preventing deep root growth of cultivated plants and causes yield instability. The mode of inheritance for grain yield and mineral absorption ratio of a diallel cross in soybeans [Glycine max (L.) Merrill] grown in high and low Al areas was identified. Differences among the genotypes for grain yield were more evident in the high Al, by grouping tolerant and non-tolerant genotypes for their respective arrays in the hybrids. A large proportion of genetic variance was additive for grain yield and mineral absorption ratio in both environments. High heritability values suggest that soybeans can be improved by crosses among Al-tolerant genotypes, using modified pedigree, early generation and recurrent selection schemes.

Genetic polymorphisms of the main transcription factors for adiponectin gene promoter in regulation of adiponectin levels: association analysis in three European cohorts.

Adiponectin serum concentrations are an important biomarker in cardiovascular epidemiology with heritability etimates of 30-70%. However, known genetic variants in the adiponectin gene locus (ADIPOQ) account for only 2%-8% of its variance. As transcription factors are thought to play an under-acknowledged role in carrying functional variants, we hypothesized that genetic polymorphisms in genes coding for the main transcription factors for the ADIPOQ promoter influence adiponectin levels. Single nucleotide polymorphisms (SNPs) at these genes were selected based on the haplotype block structure and previously published evidence to be associated with adiponectin levels. We performed association analyses of the 24 selected SNPs at forkhead box O1 (FOXO1), sterol-regulatory-element-binding transcription factor 1 (SREBF1), sirtuin 1 (SIRT1), peroxisome-proliferator-activated receptor gamma (PPARG) and transcription factor activating enhancer binding protein 2 beta (TFAP2B) gene loci with adiponectin levels in three different European cohorts: SAPHIR (n = 1742), KORA F3 (n = 1636) and CoLaus (n = 5355). In each study population, the association of SNPs with adiponectin levels on log-scale was tested using linear regression adjusted for age, sex and body mass index, applying both an additive and a recessive genetic model. A pooled effect size was obtained by meta-analysis assuming a fixed effects model. We applied a significance threshold of 0.0033 accounting for the multiple testing situation. A significant association was only found for variants within SREBF1 applying an additive genetic model (smallest p-value for rs1889018 on log(adiponectin) = 0.002, β on original scale = -0.217 µg/ml), explaining ∼0.4% of variation of adiponectin levels. Recessive genetic models or haplotype analyses of the FOXO1, SREBF1, SIRT1, TFAPB2B genes or sex-stratified analyses did not reveal additional information on the regulation of adiponectin levels. The role of genetic variations at the SREBF1 gene in regulating adiponectin needs further investigation by functional studies.

Looking for Validity or Testing It? The Perils of Stepwise Regression, Extreme-Scores Analysis, Heteroscedasticity, and Measurement Error

When researchers introduce a new test they have to demonstrate that it is valid, using unbiased designs and suitable statistical procedures. In this article we use Monte Carlo analyses to highlight how incorrect statistical procedures (i.e., stepwise regression, extreme scores analyses) or ignoring regression assumptions (e.g., heteroscedasticity) contribute to wrong validity estimates. Beyond these demonstrations, and as an example, we re-examined the results reported by Warwick, Nettelbeck, and Ward (2010) concerning the validity of the Ability Emotional Intelligence Measure (AEIM). Warwick et al. used the wrong statistical procedures to conclude that the AEIM was incrementally valid beyond intelligence and personality traits in predicting various outcomes. In our re-analysis, we found that the reliability-corrected multiple correlation of their measures with personality and intelligence was up to .69. Using robust statistical procedures and appropriate controls, we also found that the AEIM did not predict incremental variance in GPA, stress, loneliness, or well-being, demonstrating the importance for testing validity instead of looking for it.

Predictive analysis and mapping of indoor radon concentrations in Switzerland

It is estimated that around 230 people die each year due to radon (222Rn) exposure in Switzerland. 222Rn occurs mainly in closed environments like buildings and originates primarily from the subjacent ground. Therefore it depends strongly on geology and shows substantial regional variations. Correct identification of these regional variations would lead to substantial reduction of 222Rn exposure of the population based on appropriate construction of new and mitigation of already existing buildings. Prediction of indoor 222Rn concentrations (IRC) and identification of 222Rn prone areas is however difficult since IRC depend on a variety of different variables like building characteristics, meteorology, geology and anthropogenic factors. The present work aims at the development of predictive models and the understanding of IRC in Switzerland, taking into account a maximum of information in order to minimize the prediction uncertainty. The predictive maps will be used as a decision-support tool for 222Rn risk management. The construction of these models is based on different data-driven statistical methods, in combination with geographical information systems (GIS). In a first phase we performed univariate analysis of IRC for different variables, namely the detector type, building category, foundation, year of construction, the average outdoor temperature during measurement, altitude and lithology. All variables showed significant associations to IRC. Buildings constructed after 1900 showed significantly lower IRC compared to earlier constructions. We observed a further drop of IRC after 1970. In addition to that, we found an association of IRC with altitude. With regard to lithology, we observed the lowest IRC in sedimentary rocks (excluding carbonates) and sediments and the highest IRC in the Jura carbonates and igneous rock. The IRC data was systematically analyzed for potential bias due to spatially unbalanced sampling of measurements. In order to facilitate the modeling and the interpretation of the influence of geology on IRC, we developed an algorithm based on k-medoids clustering which permits to define coherent geological classes in terms of IRC. We performed a soil gas 222Rn concentration (SRC) measurement campaign in order to determine the predictive power of SRC with respect to IRC. We found that the use of SRC is limited for IRC prediction. The second part of the project was dedicated to predictive mapping of IRC using models which take into account the multidimensionality of the process of 222Rn entry into buildings. We used kernel regression and ensemble regression tree for this purpose. We could explain up to 33% of the variance of the log transformed IRC all over Switzerland. This is a good performance compared to former attempts of IRC modeling in Switzerland. As predictor variables we considered geographical coordinates, altitude, outdoor temperature, building type, foundation, year of construction and detector type. Ensemble regression trees like random forests allow to determine the role of each IRC predictor in a multidimensional setting. We found spatial information like geology, altitude and coordinates to have stronger influences on IRC than building related variables like foundation type, building type and year of construction. Based on kernel estimation we developed an approach to determine the local probability of IRC to exceed 300 Bq/m3. In addition to that we developed a confidence index in order to provide an estimate of uncertainty of the map. All methods allow an easy creation of tailor-made maps for different building characteristics. Our work is an essential step towards a 222Rn risk assessment which accounts at the same time for different architectural situations as well as geological and geographical conditions. For the communication of 222Rn hazard to the population we recommend to make use of the probability map based on kernel estimation. The communication of 222Rn hazard could for example be implemented via a web interface where the users specify the characteristics and coordinates of their home in order to obtain the probability to be above a given IRC with a corresponding index of confidence. Taking into account the health effects of 222Rn, our results have the potential to substantially improve the estimation of the effective dose from 222Rn delivered to the Swiss population.

Violent adolescents and their educational environment: a multilevel analysis.

OBJECTIVE: This study examined the respective roles of personal and environmental factors in youth violence in a nationally representative sample of 7548 postmandatory school students and apprentices ages 16-20 years in Switzerland. METHODS: Youth violence was defined as having committed at least one of the following in the previous 12 months: attacking an adult, snatching something, carrying a weapon, or using a weapon in a fight. Different ecological levels were tested, resulting in a three-level model only in males (individual, classroom, and school) as the low prevalence of female violence did not allow for a multilevel analysis. Dependent variables were attributed to each level. For males, the classroom level (10%) and the school level (24%) accounted for more than one third in interindividual variance. RESULTS: Factors associated with violence perpetration in females were being a victim of physical violence and sensation seeking at the individual level. In males, practicing unsafe sex, sensation seeking, being a victim of physical violence, having a poor relationship with parents, being depressed, and living in a single-parent household at the individual level; violence and antisocial acts at the classroom level; and being in a vocational school at the school level showed a correlation with violence perpetration. CONCLUSION: Interventions at the classroom level as well as an explicit school policy on violence and other risk behaviors should be considered a priority when dealing with the problem of youth violence. Furthermore, prevention should take into account gender differences.

Pharmacogenetics-based population pharmacokinetic analysis of etravirine in HIV-1 infected individuals.

OBJECTIVES: Etravirine (ETV) is metabolized by cytochrome P450 (CYP) 3A, 2C9, and 2C19. Metabolites are glucuronidated by uridine diphosphate glucuronosyltransferases (UGT). To identify the potential impact of genetic and non-genetic factors involved in ETV metabolism, we carried out a two-step pharmacogenetics-based population pharmacokinetic study in HIV-1 infected individuals. MATERIALS AND METHODS: The study population included 144 individuals contributing 289 ETV plasma concentrations and four individuals contributing 23 ETV plasma concentrations collected in a rich sampling design. Genetic variants [n=125 single-nucleotide polymorphisms (SNPs)] in 34 genes with a predicted role in ETV metabolism were selected. A first step population pharmacokinetic model included non-genetic and known genetic factors (seven SNPs in CYP2C, one SNP in CYP3A5) as covariates. Post-hoc individual ETV clearance (CL) was used in a second (discovery) step, in which the effect of the remaining 98 SNPs in CYP3A, P450 cytochrome oxidoreductase (POR), nuclear receptor genes, and UGTs was investigated. RESULTS: A one-compartment model with zero-order absorption best characterized ETV pharmacokinetics. The average ETV CL was 41 (l/h) (CV 51.1%), the volume of distribution was 1325 l, and the mean absorption time was 1.2 h. The administration of darunavir/ritonavir or tenofovir was the only non-genetic covariate influencing ETV CL significantly, resulting in a 40% [95% confidence interval (CI): 13-69%] and a 42% (95% CI: 17-68%) increase in ETV CL, respectively. Carriers of rs4244285 (CYP2C19*2) had 23% (8-38%) lower ETV CL. Co-administered antiretroviral agents and genetic factors explained 16% of the variance in ETV concentrations. None of the SNPs in the discovery step influenced ETV CL. CONCLUSION: ETV concentrations are highly variable, and co-administered antiretroviral agents and genetic factors explained only a modest part of the interindividual variability in ETV elimination. Opposing effects of interacting drugs effectively abrogate genetic influences on ETV CL, and vice-versa.

Une méta-analyse GWA de la glycémie après 2h d'HGPO révèle que GIPR est associé avec la sécrétion de l'insuline en réponse au glucose et que l'ADCY5 est un nouveau gène de suseptibilité au diabète de type 2. [A meta-analysis of GWA blood glucose after 2 h of OGTT revealed that GIPR is associated with the secretion of insulin based on glucose and ADCY5 is a new susceptibility gene for type 2 diabetes.]

Introduction: Les études GVvA (Genome-wide association ,-studies) ont identifié et confirmé plus de 20 gènes de susceptibilité au DT2 et ont contribué à mieux comprendre sa physiopathologie. L'hyperglycémie à jeun (GJ), et 2 heures après une HGPO (G2h) sont les deux mesures cliniques du diagnostic du DT2. Nous avons identifié récemment la G6P du pancréas (G6PC2) comme déterminant de la variabilité physiologique de la GJ puis Ie récepteur à la mélatonine (MTNRIB) qui de plus lie la régulation du rythme circadien au DT2. Dans ce travail nous avons étudié la génétique de la G2h à l'aide de l'approche GWA. Résultats: Nous avons réalisé une méta-analyse GWA dans le cadre de MAGIC (Meta-Analysis of Glucose and Insulin related traits Consortium) qui a inclus 9 études GWA (N=15'234). La réplication de 29 loci (N=6958-30 121, P < 10-5 ) a confirmé 5 nouveaux loci; 2 étant connus comme associés avec Ie DT2 (TCF7L2, P = 1,6 X 10-10 ) et la GJ (GCKR, p = 5,6 X 10-10 ); alors que GIPR (p= 5,2 X 10-12), VSP13C (p= 3,9 X 10-8) et ADCY5 (p = 1,11 X 10-15 ) sont inédits. GIPR code Ie récepteur au GIP (gastric inhibitory polypeptide) qui est sécrété par les ceIlules intestinales pour stimuler la sécrétion de l'insuline en réponse au glucose (l'effet incrétine). Les porteurs du variant GIPR qui augmente la G2h ont également un indice insulinogénique plus bas, (p= 1,0 X 10-17) mais ils ne présentent aucune modification de leur glycémie suite à une hyperglycémie provoquée par voie veineuse (p= 0,21). Ces résultats soutiennent un effet incrétine du locus GIPR qui expliquerait ~9,6 % de la variance total de ce trait. La biologie de ADCY5 et VPS13C et son lien avec l'homéostasie du glucose restent à élucider. GIPR n'est pas associé avec le risque de DT2 indiquant qu'il influence la variabilité physiologique de la G2h alors que le locus ADCY5 est associé avec le DT2 (OR = 1,11, P = 1,5 X 10-15). Conclusion: Notre étude démontre que l'étude de la G2h est une approche efficace d'une part pour la compréhension de la base génétique de la physiologie de ce trait clinique important et d'autre part pour identifier de nouveaux gènes de susceptibilité au DT2.

Biometrical analysis and selection of tetraploid progenies of Panicum maximum using mixed model methods

The objectives of this work were to estimate the genetic and phenotypic parameters and to predict the genetic and genotypic values of the selection candidates obtained from intraspecific crosses in Panicum maximum as well as the performance of the hybrid progeny of the existing and projected crosses. Seventy-nine intraspecific hybrids obtained from artificial crosses among five apomictic and three sexual autotetraploid individuals were evaluated in a clonal test with two replications and ten plants per plot. Green matter yield, total and leaf dry matter yields and leaf percentage were evaluated in five cuts per year during three years. Genetic parameters were estimated and breeding and genotypic values were predicted using the restricted maximum likelihood/best linear unbiased prediction procedure (REML/BLUP). The dominant genetic variance was estimated by adjusting the effect of full-sib families. Low magnitude individual narrow sense heritabilities (0.02-0.05), individual broad sense heritabilities (0.14-0.20) and repeatability measured on an individual basis (0.15-0.21) were obtained. Dominance effects for all evaluated characteristics indicated that breeding strategies that explore heterosis must be adopted. Less than 5% increase in the parameter repeatability was obtained for a three-year evaluation period and may be the criterion to determine the maximum number of years of evaluation to be adopted, without compromising gain per cycle of selection. The identification of hybrid candidates for future cultivars and of those that can be incorporated into the breeding program was based on the genotypic and breeding values, respectively. The prediction of the performance of the hybrid progeny, based on the breeding values of the progenitors, permitted the identification of the best crosses and indicated the best parents to use in crosses.

Docetaxel and gemcitabine combination in 133 advanced soft-tissue sarcomas: a retrospective analysis.

Advanced soft-tissue sarcomas are usually resistant to cytotoxic agents such as doxorubicin and ifosfamide. Antitumor activity has been observed for gemcitabine and docetaxel combination. We conducted a retrospective study on 133 patients (58 males/75 females) with unresectable or metastatic soft-tissue sarcoma. The median age at diagnosis was 51.7 (18-82), with 76 patients with leiomoyosarcoma and 57 patients with other histological subtypes. The initial localizations were limb (44), uterine (32), retroperitoneal (23) and organs or bone (34). Patients received 900 mg/m2 of gemcitabine (days 1 and 8) over 90 min plus 100 mg/m2 of docetaxel (day 8), intravenously every 21 days. Gemcitabine/docetaxel combination was well tolerated with an overall response of 18.4% and with no clear statistical difference between leiomyosarcomas and other histological subtypes (24.2% versus 10.4% (p=0.06)). No difference was found between uterine soft-tissue sarcomas versus others. The median overall survival was 12.1 months (1-28). Better overall survival was correlated with leiomyosarcoma (p=0.01) and with the quality of the response, even for patients with stable disease (p<10(-4)). No statistical difference was found for the initial localization. Response to treatment and overall survival were better for patients in World Health Organization (WHO) performance status classification (PS) 0 at baseline versus patients in WHO PS-1, 2 or 3 (p=0.023 and p<10(-4), respectively). Gemcitabine/docetaxel combination was tolerable and demonstrated better response and survival for leiomyosarcoma, especially for patients in WHO PS-0 at baseline. For the other histological subtypes, the response was not encouraging, but the survival for patients in response or stable suggests further investigation.

Density, climate and varying return points: an analysis of long-term population fluctuations in the threatened European tree frog.

Experimental research has identified many putative agents of amphibian decline, yet the population-level consequences of these agents remain unknown, owing to lack of information on compensatory density dependence in natural populations. Here, we investigate the relative importance of intrinsic (density-dependent) and extrinsic (climatic) factors impacting the dynamics of a tree frog (Hyla arborea) population over 22 years. A combination of log-linear density dependence and rainfall (with a 2-year time lag corresponding to development time) explain 75% of the variance in the rate of increase. Such fluctuations around a variable return point might be responsible for the seemingly erratic demography and disequilibrium dynamics of many amphibian populations.

Optimal stop-loss reinsurance: a dependence analysis

The stop-loss reinsurance is one of the most important reinsurance contracts in the insurance market. From the insurer point of view, it presents an interesting property: it is optimal if the criterion of minimizing the variance of the cost of the insurer is used. The aim of the paper is to contribute to the analysis of the stop-loss contract in one period from the point of view of the insurer and the reinsurer. Firstly, the influence of the parameters of the reinsurance contract on the correlation coefficient between the cost of the insurer and the cost of the reinsurer is studied. Secondly, the optimal stop-loss contract is obtained if the criterion used is the maximization of the joint survival probability of the insurer and the reinsurer in one period.

Ecological-niche factor analysis: how to compute habitat-suitability maps without absence data?

We propose a multivariate approach to the study of geographic species distribution which does not require absence data. Building on Hutchinson's concept of the ecological niche, this factor analysis compares, in the multidimensional space of ecological variables, the distribution of the localities where the focal species was observed to a reference set describing the whole study area. The first factor extracted maximizes the marginality of the focal species, defined as the ecological distance between the species optimum and the mean habitat within the reference area. The other factors maximize the specialization of this focal species, defined as the ratio of the ecological variance in mean habitat to that observed for the focal species. Eigenvectors and eigenvalues are readily interpreted and can be used to build habitat-suitability maps. This approach is recommended in Situations where absence data are not available (many data banks), unreliable (most cryptic or rare species), or meaningless (invaders). We provide an illustration and validation of the method for the alpine ibex, a species reintroduced in Switzerland which presumably has not yet recolonized its entire range.

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.