Post-surgical follow-up of primary hyperparathyroidism associated with multiple endocrine neoplasia type 1

The bone mineral density increments in patients with sporadic primary hyperparathyroidism after parathyroidectomy have been studied by several investigators, but few have investigated this topic in primary hyperparathyroidism associated with multiple endocrine neoplasia type 1. Further, as far as we know, only two studies have consistently evaluated bone mineral density values after parathyroidectomy in cases of primary hyperparathyroidism associated with multiple endocrine neoplasia type 1. Here we revised the impact of parathyroidectomy (particularly total parathyroidectomy followed by autologous parathyroid implant into the forearm) on bone mineral density values in patients with primary hyperparathyroidism associated with multiple endocrine neoplasia type 1. Significant increases in bone mineral density in the lumbar spine and femoral neck values were found, although no short-term (15 months) improvement in bone mineral density at the proximal third of the distal radius was observed. Additionally, short-term and medium-term calcium and parathyroid hormone values after parathyroidectomy in patients with primary hyperparathyroidism associated with multiple endocrine neoplasia type 1 are discussed. In most cases, this surgical approach was able to restore normal calcium/parathyroid hormone levels and ultimately lead to discontinuation of calcium and calcitriol supplementation.

Binding of the wheat germ lectin to Cryptococcus neoformans chitooligomers affects multiple mechanisms required for fungal pathogenesis

The principal capsular component of Cryptococcus neoformans, glucuronoxylomannan (GXM), interacts with surface glycans, including chitin-like oligomers. Although the role of GXM in cryptococcal infection has been well explored, there is no information on how chitooligomers affect fungal pathogenesis. In this study, surface chitooligomers of C. neoformans were blocked through the use of the wheat germ lectin (WGA) and the effects on animal pathogenesis, interaction with host cells, fungal growth and capsule formation were analyzed. Treatment of C. neoformans cells with WGA followed by infection of mice delayed mortality relative to animals infected with untreated fungal cells. This observation was associated with reduced brain colonization by lectin-treated cryptococci. Blocking chitooligomers also rendered yeast cells less efficient in their ability to associate with phagocytes. WGA did not affect fungal viability, but inhibited GXM release to the extracellular space and capsule formation. In WGA-treated yeast cells, genes that are involved in capsule formation and GXM traffic had their transcription levels decreased in comparison with untreated cells. Our results suggest that cellular pathways required for capsule formation and pathogenic mechanisms are affected by blocking chitin-derived structures at the cell surface of C. neoformans. Targeting chitooligomers with specific ligands may reveal new therapeutic alternatives to control cryptococcosis.

Multiple testing in spatial epidemiology: a Bayesian approach

In this work we aim to propose a new approach for preliminary epidemiological studies on Standardized Mortality Ratios (SMR) collected in many spatial regions. A preliminary study on SMRs aims to formulate hypotheses to be investigated via individual epidemiological studies that avoid bias carried on by aggregated analyses. Starting from collecting disease counts and calculating expected disease counts by means of reference population disease rates, in each area an SMR is derived as the MLE under the Poisson assumption on each observation. Such estimators have high standard errors in small areas, i.e. where the expected count is low either because of the low population underlying the area or the rarity of the disease under study. Disease mapping models and other techniques for screening disease rates among the map aiming to detect anomalies and possible high-risk areas have been proposed in literature according to the classic and the Bayesian paradigm. Our proposal is approaching this issue by a decision-oriented method, which focus on multiple testing control, without however leaving the preliminary study perspective that an analysis on SMR indicators is asked to. We implement the control of the FDR, a quantity largely used to address multiple comparisons problems in the eld of microarray data analysis but which is not usually employed in disease mapping. Controlling the FDR means providing an estimate of the FDR for a set of rejected null hypotheses. The small areas issue arises diculties in applying traditional methods for FDR estimation, that are usually based only on the p-values knowledge (Benjamini and Hochberg, 1995; Storey, 2003). Tests evaluated by a traditional p-value provide weak power in small areas, where the expected number of disease cases is small. Moreover tests cannot be assumed as independent when spatial correlation between SMRs is expected, neither they are identical distributed when population underlying the map is heterogeneous. The Bayesian paradigm oers a way to overcome the inappropriateness of p-values based methods. Another peculiarity of the present work is to propose a hierarchical full Bayesian model for FDR estimation in testing many null hypothesis of absence of risk.We will use concepts of Bayesian models for disease mapping, referring in particular to the Besag York and Mollié model (1991) often used in practice for its exible prior assumption on the risks distribution across regions. The borrowing of strength between prior and likelihood typical of a hierarchical Bayesian model takes the advantage of evaluating a singular test (i.e. a test in a singular area) by means of all observations in the map under study, rather than just by means of the singular observation. This allows to improve the power test in small areas and addressing more appropriately the spatial correlation issue that suggests that relative risks are closer in spatially contiguous regions. The proposed model aims to estimate the FDR by means of the MCMC estimated posterior probabilities b i's of the null hypothesis (absence of risk) for each area. An estimate of the expected FDR conditional on data (\FDR) can be calculated in any set of b i's relative to areas declared at high-risk (where thenull hypothesis is rejected) by averaging the b i's themselves. The\FDR can be used to provide an easy decision rule for selecting high-risk areas, i.e. selecting as many as possible areas such that the\FDR is non-lower than a prexed value; we call them\FDR based decision (or selection) rules. The sensitivity and specicity of such rule depend on the accuracy of the FDR estimate, the over-estimation of FDR causing a loss of power and the under-estimation of FDR producing a loss of specicity. Moreover, our model has the interesting feature of still being able to provide an estimate of relative risk values as in the Besag York and Mollié model (1991). A simulation study to evaluate the model performance in FDR estimation accuracy, sensitivity and specificity of the decision rule, and goodness of estimation of relative risks, was set up. We chose a real map from which we generated several spatial scenarios whose counts of disease vary according to the spatial correlation degree, the size areas, the number of areas where the null hypothesis is true and the risk level in the latter areas. In summarizing simulation results we will always consider the FDR estimation in sets constituted by all b i's selected lower than a threshold t. We will show graphs of the\FDR and the true FDR (known by simulation) plotted against a threshold t to assess the FDR estimation. Varying the threshold we can learn which FDR values can be accurately estimated by the practitioner willing to apply the model (by the closeness between\FDR and true FDR). By plotting the calculated sensitivity and specicity (both known by simulation) vs the\FDR we can check the sensitivity and specicity of the corresponding\FDR based decision rules. For investigating the over-smoothing level of relative risk estimates we will compare box-plots of such estimates in high-risk areas (known by simulation), obtained by both our model and the classic Besag York Mollié model. All the summary tools are worked out for all simulated scenarios (in total 54 scenarios). Results show that FDR is well estimated (in the worst case we get an overestimation, hence a conservative FDR control) in small areas, low risk levels and spatially correlated risks scenarios, that are our primary aims. In such scenarios we have good estimates of the FDR for all values less or equal than 0.10. The sensitivity of\FDR based decision rules is generally low but specicity is high. In such scenario the use of\FDR = 0:05 or\FDR = 0:10 based selection rule can be suggested. In cases where the number of true alternative hypotheses (number of true high-risk areas) is small, also FDR = 0:15 values are well estimated, and \FDR = 0:15 based decision rules gains power maintaining an high specicity. On the other hand, in non-small areas and non-small risk level scenarios the FDR is under-estimated unless for very small values of it (much lower than 0.05); this resulting in a loss of specicity of a\FDR = 0:05 based decision rule. In such scenario\FDR = 0:05 or, even worse,\FDR = 0:1 based decision rules cannot be suggested because the true FDR is actually much higher. As regards the relative risk estimation, our model achieves almost the same results of the classic Besag York Molliè model. For this reason, our model is interesting for its ability to perform both the estimation of relative risk values and the FDR control, except for non-small areas and large risk level scenarios. A case of study is nally presented to show how the method can be used in epidemiology.

Predictive Ability of NGAL as a Marker of Renal Damage: evaluation of Multiple Clinical Settings

Introduction. Neutrophil Gelatinase-Associated Lipocalin (NGAL) belongs to the family of lipocalins and it is produced by several cell types, including renal tubular epithelium. In the kidney its production increases during acute damage and this is reflected by the increase in serum and urine levels. In animal studies and clinical trials, NGAL was found to be a sensitive and specific indicator of acute kidney injury (AKI). Purpose. The aim of this work was to investigate, in a prospective manner, whether urine NGAL can be used as a marker in preeclampsia, kidney transplantation, VLBI and diabetic nephropathy. Materials and methods. The study involved 44 consecutive patients who received renal transplantation; 18 women affected by preeclampsia (PE); a total of 55 infants weighing ≤1500 g and 80 patients with Type 1 diabetes. Results. A positive correlation was found between urinary NGAL and 24 hours proteinuria within the PE group. The detection of higher uNGAL values in case of severe PE, even in absence of statistical significance, confirms that these women suffer from an initial renal damage. In our population of VLBW infants, we found a positive correlation of uNGAL values at birth with differences in sCreat and eGFR values from birth to day 21, but no correlation was found between uNGAL values at birth and sCreat and eGFR at day 7. systolic an diastolic blood pressure decreased with increasing levels of uNGAL. The patients with uNGAL <25 ng/ml had significantly higher levels of systolic blood pressure compared with the patients with uNGAL >50 ng/ml ( p<0.005). Our results indicate the ability of NGAL to predict the delay in functional recovery of the graft. Conclusions. In acute renal pathology, urinary NGAL confirms to be a valuable predictive marker of the progress and status of acute injury.

Modulation of hypoxia-inducible factors as a therapeutic target for multiple myeloma

Hypoxia-inducible factor-1 alpha (HIF-1α) plays a critical role in survival and is associated with poor prognosis in solid tumors. The role of HIF-1α in multiple myeloma is not completely known. In the present study, we explored the effect of EZN2968, an locked nucleic acid antisense oligonucleotide against HIF-1α, as a molecular target in MM. A panel of MM cell lines and primary samples from MM patients were cultured in vitro in the presence of EZN2968 . Under normoxia culture condition, HIF-1α mRNA and protein expression was detectable in all MM cell lines and in CD138+ cells from newly diagnosed MM patients samples. Significant up-regulation of HIF-1α protein expression was observed after incubation with IL6 or IGF-I, confirming that HIF-1α can be further induced by biological stimuli. EZN2968 efficiently induces a selective and stable down-modulation of HIF-1α and decreased the secretion of VEGF released by MM cell. Treatment with EZN2968 gave rise to a progressive accumulation of cells in the S and subG0 phase. The analysis of p21, a cyclin-dependent kinase inhibitors controlling cell cycle check point, shows upregulation of protein levels. These results suggest that HIF-1α inhibition is sufficient for cell cycle arrest in normoxia, and for inducing an apoptotic pathways.. In the presence of bone marrow microenvironment, HIF-1α inhibition blocks MAPK kinase pathway and secretion of pro-surviaval cytokines ( IL6,VEGF,IL8) In this study we provide evidence that HIF-1α, even in the absence of hypoxia signal, is expressed in MM plasma cells and further inducible by bone marrow milieu stimuli; moreover its inhibition is sufficient to induce a permanent cell cycle arrest. Our data support the hypothesis that HIF-1α inhibition may suppress tumor growth by preventing proliferation of plasma cells through p21 activation and blocking pro-survival stimuli from bone marrow microenvironment.

The impact of intraclonal heterogeneity on the outcomes of Multiple Myeloma patients treated with new drugs

Understanding the biology of Multiple Myeloma (MM) is of primary importance in the struggle to achieve a cure for this yet incurable neoplasm. A better knowledge of the mechanism underlying the development of MM can guide us in the development of new treatment strategies. Studies both on solid and haematological tumours have shown that cancer comprises a collection of related but subtly different clones, a feature that has been termed “intra-clonal heterogeneity”. This intra-clonal heterogeneity is likely, from a “Darwinian” natural selection perspective, to be the essential substrate for cancer evolution, disease progression and relapse. In this context the critical mechanism for tumour progression is competition between individual clones (and cancer stem cells) for the same microenvironmental “niche”, combined with the process of adaptation and natural selection. The Darwinian behavioural characteristics of cancer stem cells are applicable to MM. The knowledge that intra-clonal heterogeneity is an important feature of tumours’ biology has changed our way to addressing cancer, now considered as a composite mixture of clones and not as a linear evolving disease. In this variable therapeutic landscape it is important for clinicians and researchers to consider the impact that evolutionary biology and intra-clonal heterogeneity have on the treatment of myeloma and the emergence of treatment resistance. It is clear that if we want to effectively cure myeloma it is of primarily importance to understand disease biology and evolution. Only by doing so will we be able to effectively use all of the new tools we have at our disposal to cure myeloma and to use treatment in the most effective way possible. The aim of the present research project was to investigate at different levels the presence of intra-clonal heterogeneity in MM patients, and to evaluate the impact of treatment on clonal evolution and on patients’ outcomes.

Nuclear receptor and nuclear receptor target gene messenger ribonucleic acid levels at different sites of the gastrointestinal tract and in liver of healthy dogs

Nuclear receptors (NR) are ligand-activated transcription factors that regulate different metabolic pathways by influencing the expression of target genes. The current study examined mRNA abundance of NR and NR target genes at different sites of the gastrointestinal tract (GIT) and the liver of healthy dogs (Beagles; n = 11). Samples of GIT and liver were collected postmortem and homogenized, total RNA was extracted and reverse transcribed, and gene expression was quantified by real-time reverse-transcription PCR relative to the mean of 3 housekeeping genes (beta-actin, glyceraldehyde-3-phosphate dehydrogenase, and ubi-quitin). Differences were observed (P < or = 0.05) in the mRNA abundance among stomach (St), duodenum (Du), jejunum (Je), ileum (Il), and colon (Col) for NR [pregnane X receptor (Du, Je > Il, Col > St), peroxisome proliferator-associated receptor gamma (St, Du, Col > Je, Il), constitutive androstane receptor (Je, Du > Il, Col), and retinoid x receptor alpha (Du > Il)] and NR target genes [glutathione-S-transferase A3-3 (Du > Je > St, Il; St > Col), phenol-sulfating phenol sulfotransferase 1A1 (Du, Je > Il, St; Col > St), cytochrome P450 3A12 (Du, Je > St, Il, Col), multiple drug resistance gene 1 (Du, Je, Il, Col > St), multiple drug resistance-associated protein 2 (Je, Du > Il > St, Col), multiple drug resistance-associated protein 3 (Col > St > Il; Du > Je, Il; St > Il), NR corepressor 2 (St > Il, Col), and cytochrome P450 reductase (St, Du, Je > Il, Col)], but not for peroxisome proliferator-associated receptor alpha. Differences (P > 0.05) in mRNA abundance in the liver relative to the GIT were also observed. In conclusion, the presence of numerous differences in expression of NR and NR target genes in different parts of the GIT and in liver of healthy dogs may be associated with location-specific functions and regulation of GIT regions.

Enantioselective analysis of ketamine and its metabolites in equine plasma and urine by CE with multiple isomer sulfated beta-CD

CE with multiple isomer sulfated beta-CD as the chiral selector was assessed for the simultaneous analysis of the enantiomers of ketamine and metabolites in extracts of equine plasma and urine. Different lots of the commercial chiral selector provided significant changes in enantiomeric ketamine separability, a fact that can be related to the manufacturing variability. A mixture of two lots was found to provide high-resolution separations and interference-free detection of the enantiomers of ketamine, norketamine, dehydronorketamine, and an incompletely identified hydroxylated metabolite of norketamine in liquid/liquid extracts of the two body fluids. Ketamine, norketamine, and dehydronorketamine could be unambiguously identified via HPLC fractionation of urinary extracts and using LC-MS and LC-MS/MS with 1 mmu mass discrimination. The CE assay was used to characterize the stereoselectivity of the compounds' enantiomers in the samples of five ponies anesthetized with isoflurane in oxygen and treated with intravenous continuous infusion of racemic ketamine. The concentrations of the ketamine enantiomers in plasma are equal, whereas the urinary amount of R-ketamine is larger than that of S-ketamine. Plasma and urine contain higher S- than R-norketamine levels and the mean S-/R-enantiomer ratios of dehydronorketamine in plasma and urine are lower than unity and similar.

Reduced Bayesian Hierarchical Models: Estimating Health Effects of Simultaneous Exposure to Multiple Pollutants

Quantifying the health effects associated with simultaneous exposure to many air pollutants is now a research priority of the US EPA. Bayesian hierarchical models (BHM) have been extensively used in multisite time series studies of air pollution and health to estimate health effects of a single pollutant adjusted for potential confounding of other pollutants and other time-varying factors. However, when the scientific goal is to estimate the impacts of many pollutants jointly, a straightforward application of BHM is challenged by the need to specify a random-effect distribution on a high-dimensional vector of nuisance parameters, which often do not have an easy interpretation. In this paper we introduce a new BHM formulation, which we call "reduced BHM", aimed at analyzing clustered data sets in the presence of a large number of random effects that are not of primary scientific interest. At the first stage of the reduced BHM, we calculate the integrated likelihood of the parameter of interest (e.g. excess number of deaths attributed to simultaneous exposure to high levels of many pollutants). At the second stage, we specify a flexible random-effect distribution directly on the parameter of interest. The reduced BHM overcomes many of the challenges in the specification and implementation of full BHM in the context of a large number of nuisance parameters. In simulation studies we show that the reduced BHM performs comparably to the full BHM in many scenarios, and even performs better in some cases. Methods are applied to estimate location-specific and overall relative risks of cardiovascular hospital admissions associated with simultaneous exposure to elevated levels of particulate matter and ozone in 51 US counties during the period 1999-2005.

Increased genome instability in Escherichia coli lon mutants: relation to emergence of multiple-antibiotic-resistant (Mar) mutants caused by insertion sequence elements and large tandem genomic amplifications

Thirteen spontaneous multiple-antibiotic-resistant (Mar) mutants of Escherichia coli AG100 were isolated on Luria-Bertani (LB) agar in the presence of tetracycline (4 microg/ml). The phenotype was linked to insertion sequence (IS) insertions in marR or acrR or unstable large tandem genomic amplifications which included acrAB and which were bordered by IS3 or IS5 sequences. Five different lon mutations, not related to the Mar phenotype, were also found in 12 of the 13 mutants. Under specific selective conditions, most drug-resistant mutants appearing late on the selective plates evolved from a subpopulation of AG100 with lon mutations. That the lon locus was involved in the evolution to low levels of multidrug resistance was supported by the following findings: (i) AG100 grown in LB broth had an important spontaneous subpopulation (about 3.7x10(-4)) of lon::IS186 mutants, (ii) new lon mutants appeared during the selection on antibiotic-containing agar plates, (iii) lon mutants could slowly grow in the presence of low amounts (about 2x MIC of the wild type) of chloramphenicol or tetracycline, and (iv) a lon mutation conferred a mutator phenotype which increased IS transposition and genome rearrangements. The association between lon mutations and mutations causing the Mar phenotype was dependent on the medium (LB versus MacConkey medium) and the antibiotic used for the selection. A previously reported unstable amplifiable high-level resistance observed after the prolonged growth of Mar mutants in a low concentration of tetracycline or chloramphenicol can be explained by genomic amplification.

Effect of interferon-beta and atorvastatin on Th1/Th2 cytokines in multiple sclerosis

Beneficial effects by both interferon-beta and statin treatment in patients with multiple sclerosis (MS) may be linked to interference with the Th1/Th2 cytokine balance. We determined patterns of Th1/Th2 cytokines (interleukin (IL)-1beta, IL-2, IL-6, IL-12p70, tumor-necrosis factor (TNF)-alpha and interferon-gamma, and IL-4, IL-5 and IL-10, respectively) in the serum of patients with relapsing-remitting MS treated with 250microg interferon-beta 1b or with interferon-beta plus 40mg atorvastatin. In treatment naïve patients with MS, a trend for lower TNF-alpha serum levels compared to controls was detected (P=0.08). Interferon-beta treatment increased TNF-alpha levels, while a trend for lowering of IL-5 serum levels was found (P=0.07). Addition of atorvastatin raised IL-12p70 serum levels (P<0.05). Mean levels of two Th2 cytokines (IL-4, IL-10) showed a non-significant increase after addition of atorvastatin. We conclude that interferon-beta and atorvastatin exert divergent action on Th1/Th2 serum cytokines levels in MS. Supplemental atorvastatin might promote a Th1-type response by raising IL-12p70. Further studies are required to support a Th2 cytokine shift by atorvastatin in patients with MS.

The Assessment of Multiple Processes Underlying the Attentional Blink: A Fixed - links Modeling Approach based on Behavioral and Electrophysiological Data

When observers are presented with two visual targets appearing in the same position in close temporal proximity, a marked reduction in detection performance of the second target has often been reported, the so-called attentional blink phenomenon. Several studies found a similar decrement of P300 amplitudes during the attentional blink period as observed with detection performances of the second target. However, whether the parallel courses of second target performances and corresponding P300 amplitudes resulted from the same underlying mechanisms remained unclear. The aim of our study was therefore to investigate whether the mechanisms underlying the AB can be assessed by fixed-links modeling and whether this kind of assessment would reveal the same or at least related processes in the behavioral and electrophysiological data. On both levels of observation three highly similar processes could be identified: an increasing, a decreasing and a u-shaped trend. Corresponding processes from the behavioral and electrophysiological data were substantially correlated, with the two u-shaped trends showing the strongest association with each other. Our results provide evidence for the assumption that the same mechanisms underlie attentional blink task performance at the electrophysiological and behavioral levels as assessed by fixed-links models.

No evidence for an association of posttraumatic stress disorder with circulating levels of CRP and IL-18 in a population-based study.

Several studies have shown associations of posttraumatic stress disorder (PTSD) with the development of cardiometabolic diseases. The underlying psychopathological mechanisms, including potential links to inflammatory processes, have been discussed but remain elusive. Therefore, the aim of the present study was to evaluate the association of PTSD symptoms with the inflammatory biomarkers C-reactive protein (CRP) and interleukin-18 (IL-18). The study population consisted of 3012 participants aged 32-81years drawn from the population-based KORA F4 study conducted in 2006-08 in the Augsburg region (Southern Germany). PTSD symptoms were measured by the Impact of Event Scale, the Posttraumatic Diagnostic Scale and interview data and classified as no, partial or full PTSD. The associations of PTSD with CRP and IL-18 concentrations were estimated by multiple regression analyses with adjustments for age, sex and cardiometabolic risk factors. Linear regression analyses showed no significant association between PTSD and CRP or IL-18 concentration: adjusted for age and sex, the geometric mean concentrations in participants with full PTSD was for CRP 9% lower and for IL-18 1% higher than in participants with no PTSD (p values 0.53 and 0.89). However, further analyses indicated that individuals with partial PTSD had an increased chance of belonging to the highest quartile of the IL-18 concentration. No significant association was observed for any of the three subscales intrusion, avoidance or hyperarousal with CRP or IL-18 concentration. This large, population-based study could not find an association of full PTSD with CRP and IL-18 concentrations. Further research is needed to analyse these relationships.

An Innovative Phase I Trial Design Allowing for the Identification of Multiple Potential Maximum Tolerated Doses with Combination Therapy of Targeted Agents

Treatment for cancer often involves combination therapies used both in medical practice and clinical trials. Korn and Simon listed three reasons for the utility of combinations: 1) biochemical synergism, 2) differential susceptibility of tumor cells to different agents, and 3) higher achievable dose intensity by exploiting non-overlapping toxicities to the host. Even if the toxicity profile of each agent of a given combination is known, the toxicity profile of the agents used in combination must be established. Thus, caution is required when designing and evaluating trials with combination therapies. Traditional clinical design is based on the consideration of a single drug. However, a trial of drugs in combination requires a dose-selection procedure that is vastly different than that needed for a single-drug trial. When two drugs are combined in a phase I trial, an important trial objective is to determine the maximum tolerated dose (MTD). The MTD is defined as the dose level below the dose at which two of six patients experience drug-related dose-limiting toxicity (DLT). In phase I trials that combine two agents, more than one MTD generally exists, although all are rarely determined. For example, there may be an MTD that includes high doses of drug A with lower doses of drug B, another one for high doses of drug B with lower doses of drug A, and yet another for intermediate doses of both drugs administered together. With classic phase I trial designs, only one MTD is identified. Our new trial design allows identification of more than one MTD efficiently, within the context of a single protocol. The two drugs combined in our phase I trial are temsirolimus and bevacizumab. Bevacizumab is a monoclonal antibody targeting the vascular endothelial growth factor (VEGF) pathway which is fundamental for tumor growth and metastasis. One mechanism of tumor resistance to antiangiogenic therapy is upregulation of hypoxia inducible factor 1α (HIF-1α) which mediates responses to hypoxic conditions. Temsirolimus has resulted in reduced levels of HIF-1α making this an ideal combination therapy. Dr. Donald Berry developed a trial design schema for evaluating low, intermediate and high dose levels of two drugs given in combination as illustrated in a recently published paper in Biometrics entitled “A Parallel Phase I/II Clinical Trial Design for Combination Therapies.” His trial design utilized cytotoxic chemotherapy. We adapted this design schema by incorporating greater numbers of dose levels for each drug. Additional dose levels are being examined because it has been the experience of phase I trials that targeted agents, when given in combination, are often effective at dosing levels lower than the FDA-approved dose of said drugs. A total of thirteen dose levels including representative high, intermediate and low dose levels of temsirolimus with representative high, intermediate, and low dose levels of bevacizumab will be evaluated. We hypothesize that our new trial design will facilitate identification of more than one MTD, if they exist, efficiently and within the context of a single protocol. Doses gleaned from this approach could potentially allow for a more personalized approach in dose selection from among the MTDs obtained that can be based upon a patient’s specific co-morbid conditions or anticipated toxicities.

Gene by BMI Interactions Influencing C-Reactive Protein Levels in European-Americans

C-Reactive Protein (CRP) is a biomarker indicating tissue damage, inflammation, and infection. High-sensitivity CRP (hsCRP) is an emerging biomarker often used to estimate an individual’s risk for future coronary heart disease (CHD). hsCRP levels falling below 1.00 mg/l indicate a low risk for developing CHD, levels ranging between 1.00 mg/l and 3.00 mg/l indicate an elevated risk, and levels exceeding 3.00 mg/l indicate high risk. Multiple Genome-Wide Association Studies (GWAS) have identified a number of genetic polymorphisms which influence CRP levels. SNPs implicated in such studies have been found in or near genes of interest including: CRP, APOE, APOC, IL-6, HNF1A, LEPR, and GCKR. A strong positive correlation has also been found to exist between CRP levels and BMI, a known risk factor for CHD and a state of chronic inflammation. We conducted a series of analyses designed to identify loci which interact with BMI to influence CRP levels in a subsample of European-Americans in the ARIC cohort. In a stratified GWA analysis, 15 genetic regions were identified as having significantly (p-value < 2.00*10-3) distinct effects on hsCRP levels between the two obesity strata: lean (18.50 kg/m2 < BMI < 24.99 kg/m2) and obese (BMI ≥ 30.00 kg/m2). A GWA analysis performed on all individuals combined (i.e. not a priori stratified for obesity status) with the inclusion of an additional parameter for BMI by gene interaction, identified 11 regions which interact with BMI to influence hsCRP levels. Two regions containing the genes GJA5 and GJA8 (on chromosome 1) and FBXO11 (on chromosome 2) were identified in both methods of analysis suggesting that these genes possibly interact with BMI to influence hsCRP levels. We speculate that atrial fibrillation (AF), age-related cataracts and the TGF-β pathway may be the biological processes influenced by the interaction of GJA5, GJA8 and FBXO11, respectively, with BMI to cause changes in hsCRP levels. Future studies should focus on the influence of gene x bmi interaction on AF, age-related cataracts and TGF-β.