Identification And Characterization Of Mediators Of Toxicity Of Aβ Oligomers By Genome Wide Screening In <i>Caenorhabditis Elegans</i>

Soluble oligomers of the amyloid-β (Aβ) protein play a key role in the pathogenesis of Alzheimer’s disease (AD), although the underlying molecular mechanisms are poorly understood. In order to search for proteins involved in the formation and/or toxicity of Aβ oligomers, a transgenic C. elegans model of AD was used in which inducible expression of Aβ oligomers results in a complete paralysis; in these worms a genetic screen following chemical mutagenesis was applied to discover the genes involved in the Aβ-dependent paralysis (forward genetics). This analysis allowed identification of a mutated clone showing a complete lack of paralysis, despite this it not bear mutations in the Aβ coding region, and accumulates Aβ transcript and protein levels comparable to that of the non-mutated strain. This is the first in vivo model in which the expression of Aβ oligomers do not result in any toxic effect. The genome of the mutated worm was then sequenced and compared with that of the control strain to search for altered genes. Two genes, with no known function, were found to bear a stop codon mutation, likely resulting in the translation of an inactive protein. The rest of the mutations were missense mutations. Among them, point mutations were observed in some genes previously correlated with nematode lifespan and ageing. In C. elegans these biological processes are coordinated by the insulin/IGF-1-like signalling (IIS) pathway, which also regulates the response of the organism to toxic aggregated proteins. Thus, the activation of the IIS pathway was investigated in control and mutated worms. As expected, Aβ expression induced the up-regulation of two genes coding for small heat shock proteins (a class of chaperons known to be involved in AD) in the control strain, whereas these genes were actually down-regulated in the mutated strain. Since heat shock proteins are known to bind Aβ oligomers, these chaperons could directly mediate the formation of toxic amyloid species. Moreover, the results of the whole genome sequencing indicate that several proteins could act as potential novel mediators of Aβ toxicity and could open up new insights for research on age-related, neurodegenerative diseases

Somatic mutations in healthy cells and age-associated diseases

Aging is a complex process that affects all living organisms. As we age, the biological functions are affected, resulting in a decline of the tissue and possibly age-related diseases. Several environmental and genetic factors have been suggested to contribute to aging. Among these factors, a progressive loss of genome integrity, caused by the occurrence of somatic mutations, is proposed as a cause of deterioration of cellular functions. The aim of this thesis was to analyze the effect of somatic mutations in healthy cells and analyze the contribution of somatic mutations to age-related diseases. In paper I, we showed that satellite cells, stem cells of the skeletal muscle, accumulate 13 somatic mutations per genome per year during adult life. Although genes expressed in the skeletal muscle were protected from mutations by the DNA repair machinery, we observed that this protection was less efficient at increased age, resulting in higher mutation load in the exons of old compared to young satellite cells. A somatic mutation identified in a satellite cell was also detected in a small percentage of the cells of the muscle biopsy, suggesting that somatic mutations propagate from satellite cells to the differentiated muscle during adult age and might contribute to its age-related decline. In paper II, we created a genetic atlas of somatic mutations in healthy cells from different tissues based on newly generated and publicly-available sequencing data. In contrast to the current view of a tissue-specific mutational profile, several cell types showed the same mutational profile despite coming from different tissues. Furthermore, two distinct cell types from the same tissue showed different mutational profiles and rates of mutation accumulation. Thanks to these data, we identified multiple factors influencing mutagen exposure and consequent mutational profiles. These factors include the cell´s localization within the tissue, the degree of differentiation and the presence of a protective stem cell niche. In addition, we identified an epithelial cell of the kidney that shows a unique distribution of mutations, characterized by mutation enrichment in highly transcribed genes. This pattern increases the chances of mutating a cancer-driver gene and is in agreement with an increased predisposition to cancer in this cell type. Finally, our analyses provide evidence of a decline of DNA-repair with aging. In paper III, we identified somatic mutations in the brain of Alzheimer´s disease (AD) patients. Using ultra-deep sequencing and tailored bioinformatics analysis, we could detect low-frequency variants in bulk tissue. In total, 2.86 Mb of candidate genes and AD-linked genomic regions were included in the study, and 11 somatic single nucleotide variants (SNVs) were identified in AD brains, but none in non-AD brains. One variant was validated and predicted to affect transcription factor binding sites upstream of the CD55 gene, possibly contributing to AD through the regulation of the complement system. In paper IV, we showed that patients with end-stage chronic kidney disease (CKD) express progerin within their arterial media, the same mutated form of the protein lamin A found in premature aging patients. Importantly, we could identify the mutation that causes progeria, the LMNA c.1824C>T, in DNA extracted from the arteries. In total, we could identify the progerin protein or the mutation in 34 of the 40 CKD patients. DNA damage and increased proliferation were detected in the CKD patients, indicating extensive vascular regeneration. Our result suggests that progenitor cells carrying LMNA c.1824C>T contribute to the vascular pathology and thereby to the disease progression observed in CKD patients. In conclusion, the work presented in this thesis provides a new understanding of the contribution of mutation accumulation in healthy cells with possible implications for aging and age-associated diseases

Exploring factors influencing the adoption of mobile healthcare technologies: perspectives from designers, consultants and users’ preferences

Purpose Today, the use of smart technologies in healthcare systems is experiencing exponential growth, and the future of healthcare is seemingly closely intertwined with such technologies. Thus, any exploration of the factors that influence human health and healthcare systems inevitably touches upon the subject of new technologies. This study aims to design a conceptual model to investigate the elements that affect individuals' openness to accepting and using mobile healthcare applications (mHealth apps) and their reciprocal effects. Design/methodology/approach After a brief review of the literature, the authors identify the influential factors in the acceptance of smart technologies in healthcare systems and present a conceptual model in this regard. Next, the authors analyze the factors and variables and the extent of their impact by a structural equation modeling (SEM) approach. The statistical population of this study consists of 421 individuals including the developers, consultants and users (i.e. patients) of mHealth apps. Data analysis was done on the statistical software SPSS v.26, while SEM was carried out using the partial least squares (PLS) method on the modeling software SmartPLS. Findings The results indicate that user, consultant and developer preferences have a positive and significant impact on time, quality of life, managing chronic conditions and cooperation, and these constructs (system performance) finally have a positive and significant impact on the acceptance of mobile healthcare technologies. Originality/value This paper shows that mHealth apps can have a remarkable role in the prevention and treatment of medical conditions, and it is strongly recommended that this technology be utilized in the studied region

New methods for studying complex diseases via genetic association studies

Genome-wide association studies (GWAS) have delivered many novel insights about the etiology of many common heritable diseases. However, in most disorders studied by GWAS, the known single nucleotide polymorphisms (SNPs) associated with the disease do not account for a large portion of the genetic factors underlying the condition. This suggests that many of the undiscovered variants contributing to the risk of common diseases have weak effects or are relatively rare. This thesis introduces novel adaptations of techniques for improving detection power for both of these types of risk variants, and reports the results of analyses applying these methods to real datasets for common diseases. Chapter 2 describes a novel approach to improve the detection of weak-effect risk variants that is based on an adaptive sampling technique known as Distilled Sensing (DS). This procedure entails utilization of a portion of the total sample to exclude from consideration regions of the genome where there is no evidence of genetic association, and then testing for association with a greatly reduced number of variants in the remaining sample. Application of the method to simulated data sets and GWAS data from studies of age-related macular degeneration (AMD) demonstrated that, in many situations, DS can have superior power over traditional meta-analysis techniques to detect weak-effect loci. Chapter 3 describes an innovative pipeline to screen for rare variants in next generation sequencing (NGS) data. Since rare variants, by definition, are likely to be present in only a few individuals even in large samples, efficient methods to screen for rare causal variants are critical for advancing the utility of NGS technology. Application of our approach, which uses family-based data to identify candidate rare variants that could explain aggregation of disease in some pedigrees, resulted in the discovery of novel protein-coding variants linked to increased risk for Alzheimer's disease (AD) in African Americans. The techniques presented in this thesis address different aspects of the "missing heritability" problem and offer efficient approaches to discover novel risk variants, and thereby facilitate development of a more complete picture of genetic risk for common diseases

2014 GREAT Day Program

SUNY Geneseo’s Eighth Annual GREAT Day.https://knightscholar.geneseo.edu/program-2007/1008/thumbnail.jp

Genetics of Dementia with Lewy Bodies

In this thesis we describe that there are differences in phenotype between familial and sporadic patients with dementia with Lewy bodies. Furthermore, this thesis provides more evidence that the APOE ɛ4 allele and that rare variants in the GBA gene and the LRP10 gene are associated with dementia with Lewy bodie

Empirical study of dimensionality reduction methodologies for classification problems

Cuando hablamos de “Dimensionality Reduction” en Informática o “Big Data” nos referimos al proceso de reducción de variables previamente examinadas de un conjunto de datos para poder así obtener un conjunto de variables menor que nos permitirá construir un modelo de datos igual o con mejor precisión y menor cantidad de datos. Con este propósito se aplican técnicas de “Feature Selection” y “Feature Extraction”, con la primera de ellas extraemos un conjunto de características importantes de un dataset mediante el uso de distintos algoritmos de “machine learning”, mientras que con la segunda obtendremos un nuevo conjunto de características obtenidas a partir de las características originales. En este trabajo de fin de grado hacemos un estudio empírico sobre las distintas metodologías para clasificación de problemas utilizando un dataset médico llamado NCS-1 de pacientes clínicos con distintas patologías médicas, estudiamos los distintos algoritmos que se pueden aplicar a cada caso determinado con dicho dataset, y finalmente con los datos obtenidos realizamos un benchmark que nos permite entender mejor los distintos modelos estudiados.When we speak about Dimensionality reduction in informatics or big data, we refer to the process of reducing the number of random variables under consideration, and so, obtaining a set of principle variables which allow us to build a data model with the same or similar accuracy and a lower amount of data. For this purpose, we apply feature selection and feature extraction techniques. With feature selection we select a subset of the original feature set using techniques of machine learning, and with feature extraction we are going to build a new set of features from the original feature set. In this Project, we are going to make an empirical study about the different methodologies for classification problems using a medical dataset called NCS-1 of clinical patients with different medical pathologies, we study the different algorithms that can be applied for each case with this dataset, and finally with obtained data developing a Benchmark to understand the different applied models.Grado en Ingeniería Informátic

Investigating the role of CLU PICALM and CR1 in Alzheimer's disease

In 2009, two large genome wide association studies (GWAS) found associations between common single nucleotide polymorphisms (SNPs) at three loci (CLU, PICALM and CR1) and Alzheimer’s disease (AD) risk. The causal variants underlying these associations and how these impact on AD susceptibility remain unclear. Target enrichment and next generation sequencing (NGS) were used to completely resequence the three associated loci in 96 AD patients in an attempt to uncover potentially causative and rare variants that may explain the observed association signals. A pipeline was developed for the handling of pooled NGS data following a comparison of several different combinations of programs. 33 exonic SNPs were found within the three genes, along with over 1000 non-coding variants. To identify the variants most likely to be affecting AD risk, a two pronged approach was adopted. The variants were imputed in a large case-control cohort (2067 cases, 7376 controls) to test for association with AD, and the likely functional consequences of the variants were assessed using in silico resources. Several of the analysed variants showed suggestive or significant association with AD in the imputed data, and/or were predicted to have consequences on the function or regulation of the genes, suggesting avenues for future research in AD genetics. The whole method of pooled, targeted NGS and prioritisation using imputed data for association testing and in silico resources for functional analysis represents a new strategy for tracking down the illusive causation of GWAS signals

A systems approach to determine how Toxoplasma gondii Infection causes neuropsychiatric disease

This thesis was previously held under moratorium from 16/03/2020 to 16/03/2022T. gondii infection acquired during life has been associated with psychoneurological disease in humans and behavioural changes in mice. However, less is known about the potential of congenitally acquired T. gondii infection, or for maternal T. gondii infection induced immune activation, to cause psychoneurological disease. The studies described herein, using LCMS (Liquid chromatography–mass spectrometry) demonstrate that adult acquired infection alters the neurochemistry and transcriptome of the brains of BALB/c mice. Notable changes to tryptophan, purine, arginine and carnitine metabolism were observed in infected mice. Congenitally infected and mice exposed to the maternal immune response to T. gondii, but not congenitally infected were found to have decreased mobility compared with control mice. Congenital T. gondii infection resulted in similar alterations in the neurochemistry of mice as seen in adult acquired infections. Some of these changes were observed, including tryptophan metabolism in mice exposed to the maternal immune response to T. gondii, but not congenitally infected. Both adult acquired T. gondii and congenital infection altered the brain transcriptome of mice relative to control uninfected mice with notable changes seen to transcripts of many immunologically important genes and enzymes in some of the metabolic pathways identified by LCMS. In addition, both adult acquired T. gondii infection, congenital infection and maternal exposure to different degrees were found to induce changes in a number of additional transcripts previously associated with psychoneurological diseases. These results demonstrate that maternal exposure to T. gondii infection during pregnancy induces a subset of neurochemical and transcriptomic changes found in mice with adult acquired and congenital T. gondii infection. The results therefore reinforce the potential of maternal immune activation to affect psychoneurological diseases and implicate T. gondii as a potential aetiological agent of this process.T. gondii infection acquired during life has been associated with psychoneurological disease in humans and behavioural changes in mice. However, less is known about the potential of congenitally acquired T. gondii infection, or for maternal T. gondii infection induced immune activation, to cause psychoneurological disease. The studies described herein, using LCMS (Liquid chromatography–mass spectrometry) demonstrate that adult acquired infection alters the neurochemistry and transcriptome of the brains of BALB/c mice. Notable changes to tryptophan, purine, arginine and carnitine metabolism were observed in infected mice. Congenitally infected and mice exposed to the maternal immune response to T. gondii, but not congenitally infected were found to have decreased mobility compared with control mice. Congenital T. gondii infection resulted in similar alterations in the neurochemistry of mice as seen in adult acquired infections. Some of these changes were observed, including tryptophan metabolism in mice exposed to the maternal immune response to T. gondii, but not congenitally infected. Both adult acquired T. gondii and congenital infection altered the brain transcriptome of mice relative to control uninfected mice with notable changes seen to transcripts of many immunologically important genes and enzymes in some of the metabolic pathways identified by LCMS. In addition, both adult acquired T. gondii infection, congenital infection and maternal exposure to different degrees were found to induce changes in a number of additional transcripts previously associated with psychoneurological diseases. These results demonstrate that maternal exposure to T. gondii infection during pregnancy induces a subset of neurochemical and transcriptomic changes found in mice with adult acquired and congenital T. gondii infection. The results therefore reinforce the potential of maternal immune activation to affect psychoneurological diseases and implicate T. gondii as a potential aetiological agent of this process