Disease | EPFL Graph Search

A disease is a particular abnormal condition that negatively affects the structure or function of all or part of an organism and is not immediately due to any external injury. Diseases are often known to be medical conditions that are associated with specific signs and symptoms. A disease may be caused by external factors such as pathogens or by internal dysfunctions. For example, internal dysfunctions of the immune system can produce a variety of different diseases, including various forms of immunodeficiency, hypersensitivity, allergies, and autoimmune disorders. In humans, disease is often used more broadly to refer to any condition that causes pain, dysfunction, distress, social problems, or death to the person affected, or similar problems for those in contact with the person. In this broader sense, it sometimes includes injuries, disabilities, disorders, syndromes, infections, isolated symptoms, deviant behaviors, and atypical variations of structure and function, while in oth

Multidisciplinary Investigation of the Gut-Brain Ecosystem in a Model of Alzheimer's Disease

Arielle Louise Planchette

The search for an understanding of the causal elements that lead to neurodegenerative diseases has motivated researchers for decades. Today, Alzheimer's disease is the most prevalent form of dementia and affects approximately fifty million people worldwide, with only 5% of patients carrying causal genetic mutations. In recent years, studies of animal models as well as observations in humans have brought the gut microbiome to the forefront of AD research, as a significant contributor to the development of Alzheimer's disease. In fact, the gut microbiome is now understood to be a modulator of health and disease in numerous areas of physiology, including energy metabolism, immunity, endocrinology, and most relevant to this thesis, brain health and cognition. The gut microbiome is a complex environment composed of symbiotic bacteria, fungi and viruses (the microbiota) that produce a wide range of signalling molecules that are interpreted both by members of the microbiota and by the host (the microbiome). The host-gut interface is an ecosystem that consists of bi-directional signals and pressures applied by both constituents in order to maintain symbiotic homeostasis. Significant deleterious effects on health occur when homeostasis is lost, which may take place due to a variety of factors. These include host genetic factors and environmental factors, such as diet. Modulation of the gut microbiome has become a potentially viable therapeutic avenue for Alzheimer's disease, though it currently remains at the early stage of discovery. In this thesis, I characterize the evolution of Alzheimer's disease in the 5xFAD mouse model, with a focus on the gut microbiome and on cognitive decline and brain biochemistry. Gut microbiota modulaiton was implemented using germ-free and low-complexity bacterial cocktails, in which I outline the effects microbiota modulation on hallmarks of AD and provide insights into the metabolite profile of the brain altered by the microbiota and AD. The work in this thesis was equally motivated by the development of diagnostic tools using microscopy techniques. Biochemical assessments of disease status and progression provide information pertaining to "what" is interacting and "how much" this affects disease. With microscopy, we may gain the additional knowledge of "where" physiological constituents are and how they interact with the surrounding environment. I describe a novel multi-modal microscopy pipeline that enables the observation of signals of interest in large volumes and at high resolution with a capacity to cross-reference regions of interest in both modalities. The pipeline, known as gutOPT, consists of a sample preparation workflow compatible with mesoscale optical projection tomography (OPT) of fluorescently-labelled targets and subsequent imaging of pre-selected regions of interest in high-resolution modalities, such as confocal microscopy.

EPFL2022

Reduced order models for the simulation of pathological heart valves

Lidia Stepanova

Numerical modeling of the human cardiovascular system (CVS) represents an active branch of research which allows the medical specialists to advance in understanding of underlined processes of blood circulation and the heart work at any scale, moreover, it helps to analyze the potential problems which can arise in the CVS by modifying the parameters inside the mathematical models. Due to inability to capture in details the pressure and flow parameters without invasion into heart chambers, the process of diagnosing heart diseases can become very complicated, the limited data on atrial pressure and cardiogram results can give only overall representation of the heart condition and the exactness of the diagnosis is based mainly on experience of the doctor. Nevertheless, the development of numerical models of CVS helps to get better understanding on processes which can cause particular disease (reverse flow leakage in heart chambers, improper contraction of heart muscles due to infarction of tissue). Mathematical model allows the analysis of all physical values of the system during the heart beat as well as possibility to adjust individual parameters specific to each patient. Therefore, it becomes an efficient tool for doctors to diagnose properly the heart disease, to assign the necessary treatment and surgery, and to predict the effect of implanting cardiac-assist devices.

2013

Genetic, metabolic, and molecular insights into the diverse outcomes of diet-induced obesity in mouse

Alexis Maximilien Bachmann

Overweight and obesity are increasingly common public health issues worldwide, leading to a wide range of diseases from metabolic syndrome to steatohepatitis and cardiovascular diseases. While the increase in the prevalence of obesity is partly attributable to changes in lifestyle (i.e. increased sedentarity and changes in eating behaviour), the metabolic and clinical impacts of these obesogenic conditions varies between sexes and genetic backgrounds. The conception of personalised treatments of obesity and its complications require a thorough understanding of the diversity of responses to environmental stimuli such as high-fat diet intake. In this thesis, by analysing nine genetically diverse mouse strains, we show that much like humans, mice respond to high-fat diet in a genetic- and sex-dependent manner. Physiological and molecular responses to high-fat diet are associated with the expression of genes involved in immunity and mitochondrial function. Finally, we find that mitochondrial function and mitochondrial supercomplex assembly may explain part of the diversity of physiological responses. By exploring the complex interactions between genetics and metabolic phenotypes via gene expression and molecular traits, we shed light on the importance of genetic background and sex in determining metabolic outcomes. In addition to providing the community with an extensive resource for optimizing future experiments, this work serves as an exemplary design for more generalizable translational studies.

EPFL2021

Multidisciplinary Investigation of the Gut-Brain Ecosystem in a Model of Alzheimer's Disease

Arielle Louise Planchette

EPFL2022