Stability and sensitivity analysis of Be-CoDiS, an epidemiological model to predict the spread of human diseases between countries. Validation with data from the 2014-16 West African Ebola Virus Disease epidemic.

Ebola virus disease is a lethal human and primate disease that requires a particular attention from the international health authorities due to important recent outbreaks in some Western African countries and isolated cases in European and North-America continents. Regarding the emergency of this situation, various decision tools, such as mathematical models, were developed to assist the authorities to focus their efforts in important factors to eradicate Ebola. In a previous work, we have proposed an original deterministic spatial-temporal model, called Be-CoDiS (Between-Countries Disease Spread), to study the evolution of human diseases within and between countries by taking into consideration the movement of people between geographical areas. This model was validated by considering numerical experiments regarding the 2014-16 West African Ebola Virus Disease epidemic. In this article, we propose to perform a stability analysis of Be-CoDiS. Our first objective is to study the equilibrium states of simplified versions of this model, limited to the cases of one an two countries, and to determine their basic reproduction ratios. Then, in order to give some recommendations for the allocation of resources used to control the disease, we perform a sensitivity analysis of those basic reproduction ratios regarding the model parameters. Finally, we validate the obtained results by considering numerical experiments based on data from the 2014-16 West African Ebola Virus Disease epidemic.

Insects, ticks and human diseases, a brief statement of facts vitally important to man,

Mode of access: Internet.

Development of the Andalusian Registry of Patients Receiving Community Case Management, for the follow-up of people with complex chronic diseases.

Background: Complex chronic diseases are a challenge for the current configuration of Health services. Case management is a service frequently provided for people with chronic conditions and despite its effectiveness in many outcomes, such as mortality or readmissions, uncertainty remains about the most effective form of team organization, structures, and the nature of the interventions. Many processes and outcomes of case management for people with complex chronic conditions cannot be addressed with the information provided by electronic clinical records. Registries are frequently used to deal with this weakness. The aim of this study was to generate a registry-based information system of patients receiving case management to identify their clinical characteristics, their context of care, events identified during their follow-up, interventions developed by case managers, and services used. Methods and design: The study was divided into three phases, covering the detection of information needs, the design and its implementation in the healthcare system, using literature review and expert consensus methods to select variables that would be included in the registry. Objective: To describe the essential characteristics of the provision of ca re lo people who receive case management (structure, process and outcomes), with special emphasis on those with complex chronic diseases. Study population: Patients from any District of Primary Care, who initiate the utilization of case management services, to avoid information bias that may occur when including subjects who have already been received the service, and whose outcomes and characteristics could not be properly collected. Results: A total of 102 variables representing structure, processes and outcomes of case management were selected for their inclusion in the registry after the consensus phase. Total sample was composed of 427 patients, of which 211 (49.4%) were women and 216 (50.6%) were men. The average functional level (Barthel lndex) was 36.18 (SD 29.02), cognitive function (Pfeiffer) showed an average of 4.37 {SD 6.57), Chat1son Comorbidity lndex, obtained a mean of 3.03 (SD 2.7) and Social Support (Duke lndex) was 34.2 % (SD 17.57). More than half of patients include in the Registry, correspond lo immobilized or transitional care for patients discharged from hospital (66.5 %). The patient's educational level was low or very low (50.4%). Caregivers overstrain (Caregiver stress index), obtained an average value of 6.09% (SD 3.53). Only 1.2 % of patients had declared their advanced directives, 58.6 had not defined the tutelage and the vast majority lived at home 98.8 %. Regarding the major events recorded at RANGE Registry, 25.8 % of the selected patients died in the first three months, 8.2 % suffered a hospital admission at least once time, 2.3%, two times, and 1.2% three times, 7.5% suffered a fall, 8.7% had pressure ulcer, 4.7% had problems with medication, and 3.3 % were institutionalized. Stroke is the more prevalent health problem recorded (25.1%), followed by hypertension (11.1%) and COPD (11.1%). Patients registered by NCMs had as main processes diabetes (16.8%) and dementia (11.3 %). The most frequent nursing diagnoses referred to the self-care deficit in various activities of daily living. Regarding to nursing interventions, described by the Nursing Intervention Classification (NIC), dementia management is the most used intervention, followed by mutual goal setting, caregiver and emotional support. Conclusions: The patient profile who receive case management services is a chronic complex patient with severe dependence, cognitive impairment, normal social support, low educational level, health problems such as stroke, hypertension or COPD, diabetes or dementia, and has an informal caregiver. At the first follow up, mortality was 19.2%, and a discrete rate of readmissions and falls.

Probiotics for the prevention/treatment of human diseases and ecological study of the intestinal microbiota

The interest in human intestinal microbiota has increased in the last 20 years and significant advances have been achieved with regard to its composition and functions. The gut microbiota contributes to the maintenance of the host health status and, since alterations in the gut microbiota have been involved in the pathogenesis/progression of some diseases, several studies have focused on the manipulation of its composition. Probiotics are a strategy to maintain/restore the correct balance of gut microbial population and to prevent/treat diseases. The aim of this thesis was to explore the possibility of probiotic supplementation for the prevention/treatment of human diseases and the related study of the intestinal microbial environment. After reviewing studies concerning the use of Bifidobacterium breve as probiotic in paediatric diseases, the effectiveness of a probiotic formulation consisting of two strains of B. breve was assessed in paediatric subjects for the prevention or alleviation of gastrointestinal disorders, including coeliac disease and paediatric obesity. As the emerging role of gut microbiota in neurological diseases, the intestinal microbial environment in amyotrophic lateral sclerosis patients compared to healthy controls and the effects of a probiotic administration were examined. Considering the role of viruses in shaping gut microbiota, gut bacteriophages and bacterial community of preterm infants were investigated. The results evidenced differences in gut microbial composition of healthy controls and diseased subjects in coeliac and amyotrophic lateral sclerosis patients. The probiotic approach was effective in restoring the microbial composition in the former, whereas, in the latter, the influence was focused only on some microbial groups. The probiotic intervention was effective in improving the glyco-insulinemic profile in obese children and in preventing gastrointestinal disorders in healthy newborns. The study of the bacterial and phage composition in preterm infants suggested a transkingdom interplay between bacteria and viruses with a reciprocal influence on their composition.

Meta-analysis of gene-level associations for rare variants based on single-variant statistics.

Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available.

STATISTICAL METHODS FOR RARE AND COMMON VARIANT ASSOCIATION STUDIES

Complex human diseases are a major challenge for biological research. The goal of my research is to develop effective methods for biostatistics in order to create more opportunities for the prevention and cure of human diseases. This dissertation proposes statistical technologies that have the ability of being adapted to sequencing data in family-based designs, and that account for joint effects as well as gene-gene and gene-environment interactions in the GWA studies. The framework includes statistical methods for rare and common variant association studies. Although next-generation DNA sequencing technologies have made rare variant association studies feasible, the development of powerful statistical methods for rare variant association studies is still underway. Chapter 2 demonstrates two adaptive weighting methods for rare variant association studies based on family data for quantitative traits. The results show that both proposed methods are robust to population stratification, robust to the direction and magnitude of the effects of causal variants, and more powerful than the methods using weights suggested by Madsen and Browning [2009]. In Chapter 3, I extended the previously proposed test for Testing the effect of an Optimally Weighted combination of variants (TOW) [Sha et al., 2012] for unrelated individuals to TOW &ndash F, TOW for Family &ndash based design. Simulation results show that TOW &ndash F can control for population stratification in wide range of population structures including spatially structured populations, is robust to the directions of effect of causal variants, and is relatively robust to percentage of neutral variants. In GWA studies, this dissertation consists of a two &ndash locus joint effect analysis and a two-stage approach accounting for gene &ndash gene and gene &ndash environment interaction. Chapter 4 proposes a novel two &ndash stage approach, which is promising to identify joint effects, especially for monotonic models. The proposed approach outperforms a single &ndash marker method and a regular two &ndash stage analysis based on the two &ndash locus genotypic test. In Chapter 5, I proposed a gene &ndash based two &ndash stage approach to identify gene &ndash gene and gene &ndash environment interactions in GWA studies which can include rare variants. The two &ndash stage approach is applied to the GAW 17 dataset to identify the interaction between KDR gene and smoking status.

Coreferentiality: A New Method for the Hypothesis-Based Analysis of Phenotypes Characterized by Multivariate Data

Many multifactorial biologic effects, particularly in the context of complex human diseases, are still poorly understood. At the same time, the systematic acquisition of multivariate data has become increasingly easy. The use of such data to analyze and model complex phenotypes, however, remains a challenge. Here, a new analytic approach is described, termed coreferentiality, together with an appropriate statistical test. Coreferentiality is the indirect relation of two variables of functional interest in respect to whether they parallel each other in their respective relatedness to multivariate reference data, which can be informative for a complex effect or phenotype. It is shown that the power of coreferentiality testing is comparable to multiple regression analysis, sufficient even when reference data are informative only to a relatively small extent of 2.5%, and clearly exceeding the power of simple bivariate correlation testing. Thus, coreferentiality testing uses the increased power of multivariate analysis, however, in order to address a more straightforward interpretable bivariate relatedness. Systematic application of this approach could substantially improve the analysis and modeling of complex phenotypes, particularly in the context of human study where addressing functional hypotheses by direct experimentation is often difficult.

The estrogen receptor 1 G594A polymorphism is associated with migraine susceptibility in two independent case/control groups

Migraine is a painful and debilitating disorder with a significant genetic component. Steroid hormones, in particular estrogen, have long been considered to play a role in migraine, as variations in hormone levels are associated with migraine onset in many sufferers of the disorder. Steroid hormones mediate their activity via hormone receptors, which have a wide tissue distribution. Estrogen receptors have been localized to the brain in regions considered to be involved in migraine pathogenesis. Hence it is possible that genetic variation in the estrogen receptor gene may play a role in migraine susceptibility. This study thus examined the estrogen receptor 1 (ESRalpha) gene for a potential role in migraine pathogenesis and susceptibility. A population-based cohort of 224 migraine sufferers and 224 matched controls were genotyped for the G594A polymorphism located in exon 8 of the ESR1 gene. Statistical analysis indicated a significant difference between migraineurs and non-migraineurs in both the allele frequencies (P=0.003) and genotype distributions (P=0.008) in this sample. An independent follow-up study was then undertaken using this marker in an additional population-based cohort of 260 migraine sufferers and 260 matched controls. This resulted in a significant association between the two groups with regard to allele frequencies (P=8x10(-6)) and genotype distributions (P=4x10(-5)). Our findings support the hypothesis that genetic variation in hormone receptors, in particular the ESR1 gene, may play a role in migraine.

Challenges to environmental toxicology and epidemiology: where do we stand and which way do we go?

Modern toxicology investigates a wide array of both old and new health hazards. Priority setting is needed to select agents for research from the plethora of exposure circumstances. The changing societies and a growing fraction of the aged have to be taken into consideration. A precise exposure assessment is of importance for risk estimation and regulation. Toxicology contributes to the exploration of pathomechanisms to specify the exposure metrics for risk estimation. Combined effects of co-existing agents are not yet sufficiently understood. Animal experiments allow a separate administration of agents which can not be disentangled by epidemiological means, but their value is limited for low exposure levels in many of today's settings. As an experimental science, toxicology has to keep pace with the rapidly growing knowledge about the language of the genome and the changing paradigms in cancer development. During the pioneer era of assembling a working draft of the human genome, toxicogenomics has been developed. Gene and pathway complexity have to be considered when investigating gene-environment interactions. For a best conduct of studies, modem toxicology needs a close liaison with many other disciplines like epidemiology and bioinformatics. (C) 2004 Elsevier Ireland Ltd. All rights reserved.

Study of tRNA modifying enzymes and codon usage bias in cancer

Recent evidences indicate that tRNA modifications and tRNA modifying enzymes may play important roles in complex human diseases such as cancer, neurological disorders and mitochondrial-linked diseases. We postulate that expression deregulation of tRNA modifying enzymes affects the level of tRNA modifications and, consequently, their function and the translation efficiency of their tRNA corresponding codons. Due to the degeneracy of the genetic code, most amino acids are encoded by two to six synonymous codons. This degeneracy and the biased usage of synonymous codons cause alterations that can span from protein folding to enhanced translation efficiency of a select gene group. In this work, we focused on cancer and performed a meta-analysis study to compare microarray gene expression profiles, reported by previous studies and evaluate the codon usage of different types of cancer where tRNA modifying enzymes were found de-regulated. A total of 36 different tRNA modifying enzymes were found de-regulated in most cancer datasets analyzed. The codon usage analysis revealed a preference for codons ending in AU for the up-regulated genes, while the down-regulated genes show a preference for GC ending codons. Furthermore, a PCA biplot analysis showed this same tendency. We also analyzed the codon usage of the datasets where the CTU2 tRNA modifying enzyme was found deregulated as this enzyme affects the wobble position (position 34) of specific tRNAs. Our data points to a distinct codon usage pattern between up and downregulated genes in cancer, which might be caused by the deregulation of specific tRNA modifying enzymes. This codon usage bias may augment the transcription and translation efficiency of some genes that otherwise, in a normal situation, would be translated less efficiently.

The human epidermal differentiation complex: cornified envelope precursors, S100 proteins and the 'fused genes' family.

  The skin is essential for survival and protects our body against biological attacks, physical stress, chemical injury, water loss, ultraviolet radiation and immunological impairment. The epidermal barrier constitutes the primordial frontline of this defense established during terminal differentiation. During this complex process proliferating basal keratinocytes become suprabasally mitotically inactive and move through four epidermal layers (basal, spinous, granular and layer, stratum corneum) constantly adapting to the needs of the respective cell layer. As a result, squamous keratinocytes contain polymerized keratin intermediate filament bundles and a water-retaining matrix surrounded by the cross-linked cornified cell envelope (CE) with ceramide lipids attached on the outer surface. These cells are concomitantly insulated by intercellular lipid lamellae and hold together by corneodesmosmes. Many proteins essential for epidermal differentiation are encoded by genes clustered on chromosomal human region 1q21. These genes constitute the 'epidermal differentiation complex' (EDC), which is divided on the basis of common gene and protein structures, in three gene families: (i) CE precursors, (ii) S100A and (iii) S100 fused genes. EDC protein expression is regulated in a gene and tissue-specific manner by a pool of transcription factors. Among them, Klf4, Grhl3 and Arnt are essential, and their deletion in mice is lethal. The importance of the EDC is further reflected by human diseases: FLG mutations are the strongest risk factor for atopic dermatitis (AD) and for AD-associated asthma, and faulty CE formation caused by TG1 deficiency causes life-threatening lamellar ichthyosis. Here, we review the EDC genes and the progress in this field.

Gene-disease network analysis reveals functional modules in mendelian, complex and environmental diseases

AbstractBACKGROUND: Scientists have been trying to understand the molecular mechanisms of diseases to design preventive and therapeutic strategies for a long time. For some diseases, it has become evident that it is not enough to obtain a catalogue of the disease-related genes but to uncover how disruptions of molecular networks in the cell give rise to disease phenotypes. Moreover, with the unprecedented wealth of information available, even obtaining such catalogue is extremely difficult.PRINCIPAL FINDINGS: We developed a comprehensive gene-disease association database by integrating associations from several sources that cover different biomedical aspects of diseases. In particular, we focus on the current knowledge of human genetic diseases including mendelian, complex and environmental diseases. To assess the concept of modularity of human diseases, we performed a systematic study of the emergent properties of human gene-disease networks by means of network topology and functional annotation analysis. The results indicate a highly shared genetic origin of human diseases and show that for most diseases, including mendelian, complex and environmental diseases, functional modules exist. Moreover, a core set of biological pathways is found to be associated with most human diseases. We obtained similar results when studying clusters of diseases, suggesting that related diseases might arise due to dysfunction of common biological processes in the cell.CONCLUSIONS: For the first time, we include mendelian, complex and environmental diseases in an integrated gene-disease association database and show that the concept of modularity applies for all of them. We furthermore provide a functional analysis of disease-related modules providing important new biological insights, which might not be discovered when considering each of the gene-disease association repositories independently. Hence, we present a suitable framework for the study of how genetic and environmental factors, such as drugs, contribute to diseases.AVAILABILITY: The gene-disease networks used in this study and part of the analysis are available at http://ibi.imim.es/DisGeNET/DisGeNETweb.html#Download

Establishment of new murine embryonic stem cell lines for the generation of mouse models of human genetic diseases

Embryonic stem cells are totipotent cells derived from the inner cell mass of blastocysts. Recently, the development of appropriate culture conditions for the differentiation of these cells into specific cell types has permitted their use as potential therapeutic agents for several diseases. In addition, manipulation of their genome in vitro allows the creation of animal models of human genetic diseases and for the study of gene function in vivo. We report the establishment of new lines of murine embryonic stem cells from preimplantation stage embryos of 129/Sv mice. Most of these cells had a normal karyotype and an XY sex chromosome composition. The pluripotent properties of the cell lines obtained were analyzed on the basis of their alkaline phosphatase activity and their capacity to form complex embryoid bodies with rhythmically contracting cardiomyocytes. Two lines, USP-1 and USP-3, with the best in vitro characteristics of pluripotency were used in chimera-generating experiments. The capacity to contribute to the germ line was demonstrated by the USP-1 cell line. This cell line is currently being used to generate mouse models of human diseases.

Delineating the molecular basis of human genetic diseases: Epigenetic and functional studies

Identifying and characterizing the genes responsible for inherited human diseases will ultimately lead to a more holistic understanding of disease pathogenesis, catalyze new diagnostic and treatment modalities, and provide insights into basic biological processes. This dissertation presents research aimed at delineating the genetic and molecular basis of human diseases through epigenetic and functional studies and can be divided into two independent areas of research. The first area of research describes the development of two high-throughput melting curve based methods to assay DNA methylation, referred to as McMSP and McCOBRA. The goal of this project was to develop DNA methylation methods that can be used to rapidly determine the DNA methylation status at a specific locus in a large number of samples. McMSP and McCOBRA provide several advantages over existing methods, as they are simple, accurate, robust, and high-throughput making them applicable to large-scale DNA methylation studies. McMSP and McCOBRA were then used in an epigenetic study of the complex disease Ankylosing spondylitis (AS). Specifically, I tested the hypothesis that aberrant patterns of DNA methylation in five AS candidate genes contribute to disease susceptibility. While no statistically significant methylation differences were observed between cases and controls, this is the first study to investigate the hypothesis that epigenetic variation contributes to AS susceptibility and therefore provides the conceptual framework for future studies. ^ In the second area of research, I performed experiments to better delimit the function of aryl hydrocarbon receptor-interacting protein-like 1 (AIPL1), which when mutated causes various forms of inherited blindness such as Leber congenital amaurosis. A yeast two-hybrid screen was performed to identify putative AIPL1-interacting proteins. After screening 2 × 106 bovine retinal cDNA library clones, 6 unique putative AIPL1-interacting proteins were identified. While these 6 AIPL1 protein-protein interactions must be confirmed, their identification is an important step in understanding the functional role of AIPL1 within the retina and will provide insight into the molecular mechanisms underlying inherited blindness. ^

Comparative mapping of the human 22q11 chromosomal region and the orthologous region in mice reveals complex changes in gene organization

The region of human chromosome 22q11 is prone to rearrangements. The resulting chromosomal abnormalities are involved in Velo-cardio-facial and DiGeorge syndromes (VCFS and DGS) (deletions), “cat eye” syndrome (duplications), and certain types of tumors (translocations). As a prelude to the development of mouse models for VCFS/DGS by generating targeted deletions in the mouse genome, we examined the organization of genes from human chromosome 22q11 in the mouse. Using genetic linkage analysis and detailed physical mapping, we show that genes from a relatively small region of human 22q11 are distributed on three mouse chromosomes (MMU6, MMU10, and MMU16). Furthermore, although the region corresponding to about 2.5 megabases of the VCFS/DGS critical region is located on mouse chromosome 16, the relative organization of the region is quite different from that in humans. Our results show that the instability of the 22q11 region is not restricted to humans but may have been present throughout evolution. The results also underscore the importance of detailed comparative mapping of genes in mice and humans as a prerequisite for the development of mouse models of human diseases involving chromosomal rearrangements.