ALDH1A2 (RALDH2) genetic variation in human congenital heart disease

Abstract Background Signaling by the vitamin A-derived morphogen retinoic acid (RA) is required at multiple steps of cardiac development. Since conversion of retinaldehyde to RA by retinaldehyde dehydrogenase type II (ALDH1A2, a.k.a RALDH2) is critical for cardiac development, we screened patients with congenital heart disease (CHDs) for genetic variation at the ALDH1A2 locus. Methods One-hundred and thirty-three CHD patients were screened for genetic variation at the ALDH1A2 locus through bi-directional sequencing. In addition, six SNPs (rs2704188, rs1441815, rs3784259, rs1530293, rs1899430) at the same locus were studied using a TDT-based association approach in 101 CHD trios. Observed mutations were modeled through molecular mechanics (MM) simulations using the AMBER 9 package, Sander and Pmemd programs. Sequence conservation of observed mutations was evaluated through phylogenetic tree construction from ungapped alignments containing ALDH8 s, ALDH1Ls, ALDH1 s and ALDH2 s. Trees were generated by the Neighbor Joining method. Variations potentially affecting splicing mechanisms were cloned and functional assays were designed to test splicing alterations using the pSPL3 splicing assay. Results We describe in Tetralogy of Fallot (TOF) the mutations Ala151Ser and Ile157Thr that change non-polar to polar residues at exon 4. Exon 4 encodes part of the highly-conserved tetramerization domain, a structural motif required for ALDH oligomerization. Molecular mechanics simulation studies of the two mutations indicate that they hinder tetramerization. We determined that the SNP rs16939660, previously associated with spina bifida and observed in patients with TOF, does not affect splicing. Moreover, association studies performed with classical models and with the transmission disequilibrium test (TDT) design using single marker genotype, or haplotype information do not show differences between cases and controls. Conclusion In summary, our screen indicates that ALDH1A2 genetic variation is present in TOF patients, suggesting a possible causal role for this gene in rare cases of human CHD, but does not support the hypothesis that variation at the ALDH1A2 locus is a significant modifier of the risk for CHD in humans.

Association of genetic variants in the promoter region of genes encoding p22phox (CYBA) and glutamate cysteine ligase catalytic subunit (GCLC) and renal disease in patients with type 1 diabetes mellitus

Background Oxidative stress is recognized as a major pathogenic factor of cellular damage caused by hyperglycemia. NOX/NADPH oxidases generate reactive oxygen species and NOX1, NOX2 and NOX4 isoforms are expressed in kidney and require association with subunit p22phox (encoded by the CYBA gene). Increased expression of p22phox was described in animal models of diabetic nephropathy. In the opposite direction, glutathione is one of the main endogenous antioxidants whose plasmatic concentrations were reported to be reduced in diabetes patients. The aim of the present investigation was to test whether functional single nucleotide polymorphisms (SNPs) in genes involved in the generation of NADPH-dependent O2•- (-675 T → A in CYBA, unregistered) and in glutathione metabolism (-129 C → T in GCLC [rs17883901] and -65 T → C in GPX3 [rs8177412]) confer susceptibility to renal disease in type 1 diabetes patients. Methods 401 patients were sorted into two groups according to the presence (n = 104) or absence (n = 196) of overt diabetic nephropathy or according to glomerular filtration rate (GFR) estimated by Modification of Diet in Renal Disease (MDRD) equation: ≥ 60 mL (n = 265) or < 60 mL/min/1.73 m2 (n = 136) and were genotyped. Results No differences were found in the frequency of genotypes between diabetic and non-diabetic subjects. The frequency of GFR < 60 mL/min was significantly lower in the group of patients carrying CYBA genotypes T/A+A/A (18.7%) than in the group carrying the T/T genotype (35.3%) (P = 0.0143) and the frequency of GFR < 60 mL/min was significantly higher in the group of patients carrying GCLC genotypes C/T+T/T (47.1%) than in the group carrying the C/C genotype (31.1%) (p = 0.0082). Logistic regression analysis identified the presence of at least one A allele of the CYBA SNP as an independent protection factor against decreased GFR (OR = 0.38, CI95% 0.14-0.88, p = 0.0354) and the presence of at least one T allele of the GCLC rs17883901 SNP as an independent risk factor for decreased GFR (OR = 2.40, CI95% 1.27-4.56, p = 0.0068). Conclusions The functional SNPs CYBA -675 T → A and GCLC rs17883901, probably associated with cellular redox imbalances, modulate the risk for renal disease in the studied population of type 1 diabetes patients and require validation in additional cohorts.

Different approaches for dealing with rare variants in family-based genetic studies: application of a Genetic Analysis Workshop 17 problem

Rare variants are becoming the new candidates in the search for genetic variants that predispose individuals to a phenotype of interest. Their low prevalence in a population requires the development of dedicated detection and analytical methods. A family-based approach could greatly enhance their detection and interpretation because rare variants are nearly family specific. In this report, we test several distinct approaches for analyzing the information provided by rare and common variants and how they can be effectively used to pinpoint putative candidate genes for follow-up studies. The analyses were performed on the mini-exome data set provided by Genetic Analysis Workshop 17. Eight approaches were tested, four using the trait’s heritability estimates and four using QTDT models. These methods had their sensitivity, specificity, and positive and negative predictive values compared in light of the simulation parameters. Our results highlight important limitations of current methods to deal with rare and common variants, all methods presented a reduced specificity and, consequently, prone to false positive associations. Methods analyzing common variants information showed an enhanced sensibility when compared to rare variants methods. Furthermore, our limited knowledge of the use of biological databases for gene annotations, possibly for use as covariates in regression models, imposes a barrier to further research.

High-throughput sequencing of small RNA transcriptomes reveals critical biological features targeted by microRNAs in cell models used for squamous cell cancer research

Abstract Background The implication of post-transcriptional regulation by microRNAs in molecular mechanisms underlying cancer disease is well documented. However, their interference at the cellular level is not fully explored. Functional in vitro studies are fundamental for the comprehension of their role; nevertheless results are highly dependable on the adopted cellular model. Next generation small RNA transcriptomic sequencing data of a tumor cell line and keratinocytes derived from primary culture was generated in order to characterize the microRNA content of these systems, thus helping in their understanding. Both constitute cell models for functional studies of microRNAs in head and neck squamous cell carcinoma (HNSCC), a smoking-related cancer. Known microRNAs were quantified and analyzed in the context of gene regulation. New microRNAs were investigated using similarity and structural search, ab initio classification, and prediction of the location of mature microRNAs within would-be precursor sequences. Results were compared with small RNA transcriptomic sequences from HNSCC samples in order to access the applicability of these cell models for cancer phenotype comprehension and for novel molecule discovery. Results Ten miRNAs represented over 70% of the mature molecules present in each of the cell types. The most expressed molecules were miR-21, miR-24 and miR-205, Accordingly; miR-21 and miR-205 have been previously shown to play a role in epithelial cell biology. Although miR-21 has been implicated in cancer development, and evaluated as a biomarker in HNSCC progression, no significant expression differences were seen between cell types. We demonstrate that differentially expressed mature miRNAs target cell differentiation and apoptosis related biological processes, indicating that they might represent, with acceptable accuracy, the genetic context from which they derive. Most miRNAs identified in the cancer cell line and in keratinocytes were present in tumor samples and cancer-free samples, respectively, with miR-21, miR-24 and miR-205 still among the most prevalent molecules at all instances. Thirteen miRNA-like structures, containing reads identified by the deep sequencing, were predicted from putative miRNA precursor sequences. Strong evidences suggest that one of them could be a new miRNA. This molecule was mostly expressed in the tumor cell line and HNSCC samples indicating a possible biological function in cancer. Conclusions Critical biological features of cells must be fully understood before they can be chosen as models for functional studies. Expression levels of miRNAs relate to cell type and tissue context. This study provides insights on miRNA content of two cell models used for cancer research. Pathways commonly deregulated in HNSCC might be targeted by most expressed and also by differentially expressed miRNAs. Results indicate that the use of cell models for cancer research demands careful assessment of underlying molecular characteristics for proper data interpretation. Additionally, one new miRNA-like molecule with a potential role in cancer was identified in the cell lines and clinical samples.

Probabilistic approaches in civil engineering: generation of random fields and structural identification with genetic algorithms

The inherent stochastic character of most of the physical quantities involved in engineering models has led to an always increasing interest for probabilistic analysis. Many approaches to stochastic analysis have been proposed. However, it is widely acknowledged that the only universal method available to solve accurately any kind of stochastic mechanics problem is Monte Carlo Simulation. One of the key parts in the implementation of this technique is the accurate and efficient generation of samples of the random processes and fields involved in the problem at hand. In the present thesis an original method for the simulation of homogeneous, multi-dimensional, multi-variate, non-Gaussian random fields is proposed. The algorithm has proved to be very accurate in matching both the target spectrum and the marginal probability. The computational efficiency and robustness are very good too, even when dealing with strongly non-Gaussian distributions. What is more, the resulting samples posses all the relevant, welldefined and desired properties of “translation fields”, including crossing rates and distributions of extremes. The topic of the second part of the thesis lies in the field of non-destructive parametric structural identification. Its objective is to evaluate the mechanical characteristics of constituent bars in existing truss structures, using static loads and strain measurements. In the cases of missing data and of damages that interest only a small portion of the bar, Genetic Algorithm have proved to be an effective tool to solve the problem.

Stochastic models and dynamic measures for the characterization of bistable circuits

During the last few years, a great deal of interest has risen concerning the applications of stochastic methods to several biochemical and biological phenomena. Phenomena like gene expression, cellular memory, bet-hedging strategy in bacterial growth and many others, cannot be described by continuous stochastic models due to their intrinsic discreteness and randomness. In this thesis I have used the Chemical Master Equation (CME) technique to modelize some feedback cycles and analyzing their properties, including experimental data. In the first part of this work, the effect of stochastic stability is discussed on a toy model of the genetic switch that triggers the cellular division, which malfunctioning is known to be one of the hallmarks of cancer. The second system I have worked on is the so-called futile cycle, a closed cycle of two enzymatic reactions that adds and removes a chemical compound, called phosphate group, to a specific substrate. I have thus investigated how adding noise to the enzyme (that is usually in the order of few hundred molecules) modifies the probability of observing a specific number of phosphorylated substrate molecules, and confirmed theoretical predictions with numerical simulations. In the third part the results of the study of a chain of multiple phosphorylation-dephosphorylation cycles will be presented. We will discuss an approximation method for the exact solution in the bidimensional case and the relationship that this method has with the thermodynamic properties of the system, which is an open system far from equilibrium.In the last section the agreement between the theoretical prediction of the total protein quantity in a mouse cells population and the observed quantity will be shown, measured via fluorescence microscopy.

Genetic engineering and preclinical evaluation of oncolytic herpes simplex viruses retargeted to cancer-specific receptors

Oncolytic virotherapy exploits the ability of viruses to infect and kill cells. It is suitable as treatment for tumors that are not accessible by surgery and/or respond poorly to the current therapeutic approach. HSV is a promising oncolytic agent. It has a large genome size able to accommodate large transgenes and some attenuated oncolytic HSVs (oHSV) are already in clinical trials phase I and II. The aim of this thesis was the generation of HSV-1 retargeted to tumor-specific receptors and detargeted from HSV natural receptors, HVEM and Nectin-1. The retargeting was achieved by inserting a specific single chain antibody (scFv) for the tumor receptor selected inside the HSV glycoprotein gD. In this research three tumor receptors were considered: epidermal growth factor receptor 2 (HER2) overexpressed in 25-30% of breast and ovarian cancers and gliomas, prostate specific membrane antigen (PSMA) expressed in prostate carcinomas and in neovascolature of solid tumors; and epidermal growth factor receptor variant III (EGFRvIII). In vivo studies on HER2 retargeted viruses R-LM113 and R-LM249 have demonstrated their high safety profile. For R-LM249 the antitumor efficacy has been highlighted by target-specific inhibition of the growth of human tumors in models of HER2-positive breast and ovarian cancer in nude mice. In a murine model of HER2-positive glioma in nude mice, R-LM113 was able to significantly increase the survival time of treated mice compared to control. Up to now, PSMA and EGFRvIII viruses (R-LM593 and R-LM613) are only characterized in vitro, confirming the specific retargeting to selected targets. This strategy has proved to be generally applicable to a broad spectrum of receptors for which a single chain antibody is available.

Gamma-secretase modulators and inhibitors in Alzheimer's disease: influence of genetic background on efficacy and mechanism of action

According to the amyloid hypothesis, Alzheimer’s disease (AD) is caused by aberrant production or clearance of the amyloid-β (Aβ) peptides, and in particular of the longer more aggregation-prone Aβ42. The Aβ peptides are generated through successive proteolytic cleavage of the amyloid precursor protein (APP) by the β-site APP cleaving enzyme (BACE) and γ-secretase. γ-secretase produces Aβ peptides with variable C-termini ranging from Aβ34 to Aβ48, presumably by sequential trimming of longer into shorter peptides. γ-secretase is a multiprotein complex consisting of at least four different proteins and the presenilin proteins (PS1 or PS2) contain the catalytic center of the complex. In 2001 several non-steroidal anti-inflammatory drugs were identified as the founding members of a new class of γ-secretase modulators (GSMs) that can selectively reduce production of Aβ42. Concomitantly, these GSMs increase Aβ38 production indicating closely coordinated generation of Aβ42 and Aβ38 and a potential precursor-product relationship between these peptides. GSMs seem to exert their activity by direct modulation of γ-secretase. Support for this hypothesis is drawn from the finding that some PS mutations associated with early-onset familial AD (FAD) can modulate the cellular response to GSMs and to γ-secretase inhibitors (GSIs), which inhibit production of all Aβ peptides and are known to directly interact with PS. A particularly interesting FAD PS mutation is PS1-ΔExon9, a complex deletion mutant that blocks endoproteolysis of PS1 and renders cells completely non-responsive to GSMs. Studies presented in this thesis show that the diminished response of PS1-ΔExon9 to GSMs is mainly caused by its lack of endoproteolytic cleavage. Furthermore, we were able to demonstrate that a reduced response to GSMs and GSIs is not limited to PS1-ΔExon9 but is a common effect of aggressive FAD-associated PS1 mutations. Surprisingly, we also found that while the Aβ42 response to GSMs is almost completely abolished by these PS1 mutations, the accompanying Aβ38 increase was indistinguishable to wild-type PS1. Finally, the reduced response to GSIs was confirmed in a mouse model with transgenic expression of an aggressive FAD-associated PS1 mutation as a highly potent GSI failed to reduce Aβ42 levels in brain of these mice. Taken together, our findings provide clear evidence for independent generation of Aβ42 and Aβ38 peptides, and argue that the sequential cleavage model might be an oversimplification of the molecular mechanism of γ-secretase. Most importantly, our results highlight the significance of genetic background in drug discovery efforts aimed at γ-secretase, and indicate that the use of cellular models with transgenic expression of FAD-associated PS mutations might confound studies of the potency and efficacy of GSMs and GSIs. Therefore, such models should be strictly avoided in the ongoing preclinical development of these promising and potentially disease-modifying therapeutics for AD.

Biomolecular studies in Alzheimer’s Disease models: investigations in vitro and in vivo

The Alzheimer’s disease (AD), the most prevalent form of age-related dementia, is a multifactorial and heterogeneous neurodegenerative disease. The molecular mechanisms underlying the pathogenesis of AD are yet largely unknown. However, the etiopathogenesis of AD likely resides in the interaction between genetic and environmental risk factors. Among the different factors that contribute to the pathogenesis of AD, amyloid-beta peptides and the genetic risk factor apoE4 are prominent on the basis of genetic evidence and experimental data. ApoE4 transgenic mice have deficits in spatial learning and memory associated with inflammation and brain atrophy. Evidences suggest that apoE4 is implicated in amyloid-beta accumulation, imbalance of cellular antioxidant system and in apoptotic phenomena. The mechanisms by which apoE4 interacts with other AD risk factors leading to an increased susceptibility to the dementia are still unknown. The aim of this research was to provide new insights into molecular mechanisms of AD neurodegeneration, investigating the effect of amyloid-beta peptides and apoE4 genotype on the modulation of genes and proteins differently involved in cellular processes related to aging and oxidative balance such as PIN1, SIRT1, PSEN1, BDNF, TRX1 and GRX1. In particular, we used human neuroblastoma cells exposed to amyloid-beta or apoE3 and apoE4 proteins at different time-points, and selected brain regions of human apoE3 and apoE4 targeted replacement mice, as in vitro and in vivo models, respectively. All genes and proteins studied in the present investigation are modulated by amyloid-beta and apoE4 in different ways, suggesting their involvement in the neurodegenerative mechanisms underlying the AD. Finally, these proteins might represent novel potential diagnostic and therapeutic targets in AD.

Generation and characterization of mouse models of Small cell lung cancer and Basal cell carcinoma for the preclinical evaluation of new therapies

Background. Human small cell lung cancer (SCLC) accounting for approximately 15-20% of all lung cancers, is an aggressive tumor with high propensity for early regional and distant metastases. Although the initial tumor rate response to chemotherapy is very high, SCLC relapses after approximately 4 months in ED and 12 months in LD. Basal cell carcinoma (BCC) is the most prevalent cancer in the western world, and its incidence is increasing worldwide. This type of cancer rarely metastasizes and the death rate is extraordinary low. Surgery is curative for most of the patients, but for those that develop locally advanced or metastatic BCC there is currently no effective treatment. Both types of cancer have been deeply investigated and genetic alterations, MYCN amplification (MA) among the most interesting, have been found. These could become targets of new pharmacological therapies. Procedures. We created and characterized novel BLI xenograft orthotopic mouse models of SCLC to evaluate the tumor onset and progression and the efficacy of new pharmacological strategies. We compared an in vitro model with a transgenic mouse model of BCC, to investigate and delineate the canonical HH signalling pathway and its connections with other molecular pathways. Results and conclusions. The orthotopic models showed latency and progression patterns similar to human disease. Chemotherapy treatments improved survival rates and validated the in vivo model. The presence of MA and overexpression were confirmed in each model and we tested the efficacy of a new MYCN inhibitor in vitro. Preliminar data of BCC models highlighted Hedgehog pathway role and underlined the importance of both in vitro and in vivo strategies to achieve a better understanding of the pathology and to evaluate the applicability of new therapeutic compounds

The genetic basis of craniofacial and dental abnormalities

The embryonic head development, including the formation of dental structures, is a complex and delicate process guided by specific genetic programs. Genetic changes and environmental factors can disturb the execution of these programs and result in abnormalities in orofacial and dental structures. Orofacial clefts and hypodontia/ oligodontia are examples of such abnormalities frequently seen in dental clinics. An insight into the mechanisms and genes involved in the formation of orofacial and dental structures has been gradually gained by genetic analysis of families and by the use of experimental vertebrate models such as the mouse and chick models. The development of novel clinical therapies for orofacial and dental pathological conditions depends very much on a detailed knowledge of the molecular and cellular processes that are involved in head formation.

Echinococcus metacestodes as laboratory models for the screening of drugs against cestodes and trematodes

Among the cestodes, Echinococcus granulosus, Echinococcus multilocularis and Taenia solium represent the most dangerous parasites. Their larval stages cause the diseases cystic echinococcosis (CE), alveolar echinococcosis (AE) and cysticercosis, respectively, which exhibit considerable medical and veterinary health concerns with a profound economic impact. Others caused by other cestodes, such as species of the genera Mesocestoides and Hymenolepis, are relatively rare in humans. In this review, we will focus on E. granulosus and E. multilocularis metacestode laboratory models and will review the use of these models in the search for novel drugs that could be employed for chemotherapeutic treatment of echinococcosis. Clearly, improved therapeutic drugs are needed for the treatment of AE and CE, and this can only be achieved through the development of medium-to-high throughput screening approaches. The most recent achievements in the in vitro culture and genetic manipulation of E. multilocularis cells and metacestodes, and the accessability of the E. multilocularis genome and EST sequence information, have rendered the E. multilocularis model uniquely suited for studies on drug-efficacy and drug target identification. This could lead to the development of novel compounds for the use in chemotherapy against echinococcosis, and possibly against diseases caused by other cestodes, and potentially also trematodes.

The quantitative genetic basis of offspring solicitation and parental response in a passerine bird with biparental care

The coevolution of parental investment and offspring solicitation is driven by partly different evolutionary interests of genes expressed in parents and their offspring. In species with biparental care, the outcome of this conflict ma!: be influenced by the sexual conflict over parental investment, Models for the resolution of such family conflicts have made so far untested assumptions about genetic variation and covariation in the parental resource provisioning response and the level of offspring solicitation. Using a combination of cross-fostering and begging playback experiments, we show that, in the great tit (Parus major), (i) the begging call intensity of nestlings depends on their common origin, suggesting genetic variation for this begging display, (ii) only mothers respond to begging calls by increased food provisioning, and (iii! the size of the parental response is positively related to the begging call intensity of nestlings in the maternal but not paternal line. This study indicates that genetic covariation, its differential expression in the maternal and paternal lines and/or early environmental and parental effects need to be taken into account when predicting the phenotypic outcome of the conflict over investment between genes expressed in each parent and the offspring. [References: 36]

USE OF HIDDEN MARKOV MODELS FOR QTL MAPPING

An important aspect of the QTL mapping problem is the treatment of missing genotype data. If complete genotype data were available, QTL mapping would reduce to the problem of model selection in linear regression. However, in the consideration of loci in the intervals between the available genetic markers, genotype data is inherently missing. Even at the typed genetic markers, genotype data is seldom complete, as a result of failures in the genotyping assays or for the sake of economy (for example, in the case of selective genotyping, where only individuals with extreme phenotypes are genotyped). We discuss the use of algorithms developed for hidden Markov models (HMMs) to deal with the missing genotype data problem.

Asymptotics for Marginal Generalized Linear Models With Sparse Correlations

Marginal generalized linear models can be used for clustered and longitudinal data by fitting a model as if the data were independent and using an empirical estimator of parameter standard errors. We extend this approach to data where the number of observations correlated with a given one grows with sample size and show that parameter estimates are consistent and asymptotically Normal with a slower convergence rate than for independent data, and that an information sandwich variance estimator is consistent. We present two problems that motivated this work, the modelling of patterns of HIV genetic variation and the behavior of clustered data estimators when clusters are large.