Dissertations / Theses on the topic 'Diabetic retinopathy'

Contexte : Le diabète de type 2 (DT2) constitue une pathologie majeure, au lourd fardeau, associ ée à de nombreuses complications, comme la rétinopathie diabétique (RD). Des facteurs modifiables, comme l’alimentation, ont déjà été identifiés pour le DT2 et la RD mais certains aspects de leurs rôles restent à préciser. Objectifs : Les objectifs de cette thèse étaient d’examiner le rôle de l’alimentation, en particulier la consommation d’acides gras (AGs), et des autres facteurs modifiables liés au mode de vie sur le risque de DT2 et de synthétiser, interpréter et analyser la relation entre l’alimentation et la RD. Résultats : Les résultats suggèrent que le rôle des AGs sur le risque de DT2 et de la RD pourrait être différent selon leur type, et même varier au sein d’un groupe comme les AG polyinsaturés (AGPI). Les résultats suggèrent aussi qu’une forte adhésion aux recommandations alimentaires n’est pas associée avec le développement d’un DT2, mais en revanche une forte adhérence aux autres recommandations de santé (concernant le tour de taille, l’activité physique et le statut tabagique) est fortement associée avec un moindre risque de DT2. On a montré qu’avoir un mode de vie sain aurait pu empêcher la survenue de plus de la moitié des cas de DT2. Conclusions : Cette thèse a permis de préciser l’importance et la complexité du rôle de l’alimentation dans le développement du DT2 et de la RD. Elle montre aussi l’impact des comportements sains dans la pathologie de DT2 et confirme que le DT2 est en grande partie, une maladie évitable. Les efforts devraient se focaliser sur la modification des comportements de santé à la fois dans la population générale et atteinte de DT2 et notamment encourager une alimentation modérée et variée
Background : Type 2 diabetes (T2D) presents a significant health burden that is associated with many complications, such as diabetic retinopathy (DR), that further burden people with diabetes. Modifiable risk factors, such as the diet, have been identified for both T2D and DR; yet certain aspects of the role of the diet remain unclear. Objectives : The main objectives of this thesis were therefore to examine the role and impact of the diet, and in particular, the consumption of fatty acids (FAs), and other modifiable behaviours on the risk of T2D and to summarize, interpret and analyze the relationship between the diet and DR using data from both the E3N and AusDiab cohort studies. Results : The results suggest that the role of FAs on the risk of T2D and DR may differ between and within subgroups, and by individual polyunsaturated fatty acids (PUFAs). The findings also suggest that strongly adhering to national dietary guidelines is not associated with the development of T2D, but strongly adhering to other recommendations for healthy behaviours (for waist circumference, physical activity and smoking) is strongly inversely associated with T2D. Modifiable behaviour could have prevented more than half of the cases of T2D. Conclusions : This work underlines the importance and the complexity of the role of the diet in the development of T2D and DR. It also illustrates the impact of healthy behaviour in the etiology of T2D and confirms that T2D is largely preventable. Efforts should focus on the modification of multiple healthy behaviours in populations, and promote diets that are moderate and widely varied

Diabetic retinopathy is the single largest cause of sight loss and blindness in 18 to 65 year olds. Screening programs for the estimated one to six per- cent of the diabetic population have been demonstrated to be cost and sight saving, howeverthere are insufficient screening resources. Automatic screen-ing systems may help solve this resource short fall. This thesis reports on research into an aspect of automatic grading of diabetic retinopathy; namely the identification of the retinal blood vessels in fundus photographs. It de-velops two vessels segmentation strategies and assess their accuracies. A literature review of retinal vascular segmentation found few results, and indicated a need for further development. The two methods for vessel segmentation were investigated in this thesis are based on mathematical morphology and neural networks. Both methodologies are verified on independently labeled data from two institutions and results are presented that characterisethe trade off betweenthe ability to identify vesseland non-vessels data. These results are based on thirty five images with their retinal vessels labeled. Of these images over half had significant pathology and or image acquisition artifacts. The morphological segmentation used ten images from one dataset for development. The remaining images of this dataset and the entire set of 20 images from the seconddataset were then used to prospectively verify generaliastion. For the neural approach, the imageswere pooled and 26 randomly chosenimageswere usedin training whilst 9 were reserved for prospective validation. Assuming equal importance, or cost, for vessel and non-vessel classifications, the following results were obtained; using mathematical morphology 84% correct classification of vascular and non-vascular pixels was obtained in the first dataset. This increased to 89% correct for the second dataset. Using the pooled data the neural approach achieved 88% correct identification accuracy. The spread of accuracies observed varied. It was highest in the small initial dataset with 16 and 10 percent standard deviation in vascular and non-vascular cases respectively. The lowest variability was observed in the neural classification, with a standard deviation of 5% for both accuracies. The less tangible outcomes of the research raises the issueof the selection and subsequent distribution of the patterns for neural network training. Unfortunately this indication would require further labeling of precisely those cases that were felt to be the most difficult. I.e. the small vessels and border conditions between pathology and the retina. The more concrete, evidence based conclusions,characterise both the neural and the morphological methods over a range of operating points. Many of these operating points are comparable to the few results presented in the literature. The advantage of the author's approach lies in the neural method's consistent as well as accurate vascular classification.

Homocysteine is a sulphur amino acid converted to methionine to a remethylation pathway and to cysteine via transulphuration patway. Its level in the blood increase with age and are associated with several pathologies: cancer, autoimmune disease, cardiovascular and neurodegenerative disorders. The present thesis has focused on the study of the relationship between elevated levels of homocysteine and the deficiency of his metabolites, focusing on folate, in the severity of diabetic retinopathy (non- proliferative and proliferative). Then it had been investigated whether retinal Hcy is associated with retinal neurodegeneration. Histopathological, molecular, and biochemical abnormalities have commonalities in Diabetes and Alzheimer s Disease (AD), which has lead to AD recently termed as "Type 3 Diabetes". Therefore, the present study has focused to evaluate the role of homocysteine in animal models of Type 2 Diabetes (Goto-Kakizaki (GK) rats) and Alzheimer Disease (TASTPM transgenic mice).

Homocysteine is a sulphur amino acid converted to methionine to a remethylation pathway and to cysteine via transulphuration patway. Its level in the blood increase with age and are associated with several pathologies: cancer, autoimmune disease, cardiovascular and neurodegenerative disorders. The present thesis has focused on the study of the relationship between elevated levels of homocysteine and the deficiency of his metabolites, focusing on folate, in the severity of diabetic retinopathy (non- proliferative and proliferative). Then it had been investigated whether retinal Hcy is associated with retinal neurodegeneration. Histopathological, molecular, and biochemical abnormalities have commonalities in Diabetes and Alzheimer s Disease (AD), which has lead to AD recently termed as "Type 3 Diabetes". Therefore, the present study has focused to evaluate the role of homocysteine in animal models of Type 2 Diabetes (Goto-Kakizaki (GK) rats) and Alzheimer Disease (TASTPM transgenic mice).

La retinopatia diabètica és una malaltia crònica i una de les principals causes de ceguesa i discapacitat visual en els pacients diabètics. L'examen ocular a través d'imatges de la retina és utilitzat pels metges per detectar les lesions relacionades amb aquesta malaltia. En aquesta tesi, explorem diferents mètodes innovadors per a la classificació automàtica del grau de malaltia utilitzant imatges del fons d'ull. Per a aquest propòsit, explorem mètodes basats en l'extracció i classificació automàtica, basades en xarxes neuronals profundes. A més, dissenyem un nou mètode per a la interpretació dels resultats. El model està concebut de manera modular per a que pugui ser utilitzat en d'altres xarxes i dominis de classificació. Demostrem experimentalment que el nostre model d'interpretació és capaç de detectar lesions de retina a la imatge únicament a partir de la informació de classificació. A més, proposem un mètode per comprimir la representació interna de la informació de la xarxa. El mètode es basa en una anàlisi de components independents sobre la informació del vector d'atributs intern de la xarxa generat pel model per a cada imatge. Usant el nostre mètode d'interpretació esmentat anteriorment també és possible visualitzar aquests components en la imatge. Finalment, presentem una aplicació experimental del nostre millor model per classificar imatges de retina d'una població diferent, concretament de l'Hospital de Reus. Els mètodes proposats arriben al nivell de rendiment de l'oftalmòleg i són capaços d'identificar amb gran detall les lesions presents en les imatges, que es dedueixen només de la informació de classificació de la imatge.
La retinopatía diabética es una enfermedad crónica y una de las principales causas de ceguera y discapacidad visual en los pacientes diabéticos. El examen ocular a través de imágenes de la retina es utilizado por los médicos para detectar las lesiones relacionadas con esta enfermedad. En esta tesis, exploramos diferentes métodos novedosos para la clasificación automática del grado de enfermedad utilizando imágenes del fondo de la retina. Para este propósito, exploramos métodos basados en la extracción y clasificación automática, basadas en redes neuronales profundas. Además, diseñamos un nuevo método para la interpretación de los resultados. El modelo está concebido de manera modular para que pueda ser utilizado utilizando otras redes y dominios de clasificación. Demostramos experimentalmente que nuestro modelo de interpretación es capaz de detectar lesiones de retina en la imagen únicamente a partir de la información de clasificación. Además, proponemos un método para comprimir la representación interna de la información de la red. El método se basa en un análisis de componentes independientes sobre la información del vector de atributos interno de la red generado por el modelo para cada imagen. Usando nuestro método de interpretación mencionado anteriormente también es posible visualizar dichos componentes en la imagen. Finalmente, presentamos una aplicación experimental de nuestro mejor modelo para clasificar imágenes de retina de una población diferente, concretamente del Hospital de Reus. Los métodos propuestos alcanzan el nivel de rendimiento del oftalmólogo y son capaces de identificar con gran detalle las lesiones presentes en las imágenes, que se deducen solo de la información de clasificación de la imagen.
Diabetic Retinopathy is a chronic disease and one of the main causes of blindness and visual impairment for diabetic patients. Eye screening through retinal images is used by physicians to detect the lesions related with this disease. In this thesis, we explore different novel methods for the automatic diabetic retinopathy disease grade classification using retina fundus images. For this purpose, we explore methods based in automatic feature extraction and classification, based on deep neural networks. Furthermore, as results reported by these models are difficult to interpret, we design a new method for results interpretation. The model is designed in a modular manner in order to generalize its possible application to other networks and classification domains. We experimentally demonstrate that our interpretation model is able to detect retina lesions in the image solely from the classification information. Additionally, we propose a method for compressing model feature-space information. The method is based on a independent component analysis over the disentangled feature space information generated by the model for each image and serves also for identifying the mathematically independent elements causing the disease. Using our previously mentioned interpretation method is also possible to visualize such components on the image. Finally, we present an experimental application of our best model for classifying retina images of a different population, concretely from the Hospital de Reus. The methods proposed, achieve ophthalmologist performance level and are able to identify with great detail lesions present on images, inferred only from image classification information.

To ensure that the resources of the health care sector are used effectively, new technologies need to be evaluated before implementation to examine if they generate health outcomes at an acceptable cost. This information can be collected by performing health economic evaluations in which the costs and health outcomes of different technologies are compared. To estimate the effect on health care budgets, there is also a need for information about the prevalence of the specific disease. Health outcomes in health economic evaluations are often measured in quality-adjusted life years (QALYs), which are calculated by multiplying the remaining life years after an intervention by a weight representing the health-related quality of life (HRQoL) during those years. This thesis aims to provide deeper knowledge of the health economic aspects of diabetic retinopathy (DR), an eye complication that affects patients with diabetes and may in the worst case lead to blindness. The focus is on three empirical and two methodological health economic research questions. The empirical research areas cover prevalence, costs, and HRQoL related to patients with DR. The methodological research questions explore the performance of different methods for estimation of QALY weights. This is of interest since it has been argued that the most common methods for estimating QALY weights may not capture all relevant vision-related aspects of quality of life. The analyses comprehend the validity of different methods for estimating QALY weights among patients with DR and if the results of one of the specific methods for estimating QALY weights, the time trade-off (TTO) exercise, are affected by patients’ subjective life expectancy (SLE). The empirical results demonstrate that DR is seen in approximately 40% and 30% of patients with type I and type II diabetes respectively, indicating that the prevalence of DR has decreased in both of these patient groups. Healthcare costs vary considerably between different severity levels of the disease, being estimated at €26, €257, €216, and €433 per patient per year for background retinopathy, proliferative diabetic retinopathy (PDR), diabetic macular oedema (DMO), and PDR combined with DMO respectively. Blindness due to DR is associated with an increased use of transportation services, caregiving services, and assistive technologies as well as productivity losses. This suggests that preventing the progression of DR may lower healthcare costs. Patients with vision impairment due to DR have lowered HRQoL in various dimensions, but the diagnosis of DR in itself has only a limited effect on HRQoL. The results on the methodological research questions show that different methods for estimating QALY weights seem to give different results. In comparison to EQ-5D, the Health Utilities Index Mark 3 (HUI-3) is the most sensitive method for detecting differences in QALY weights due to DR, and if decisions are to be made based on values from the general public, it can be recommended for use in cost-utility analyses of interventions directed at DR. Neither of the direct methods, TTO and the visual analogue scale, seems to be sensitive to differences in visual function, and more research is needed concerning the role of vision in people’s responses to the TTO exercises. In TTO exercises with time frames based on actuarial life expectancy, the patients’ SLE has an effect on their willingness to trade off years for full health. Thus, applying time frames deviating from patients’ SLE may result in biased QALY weights. Such bias may appear stronger within patient populations than within the general public. In conclusion, this thesis offers estimates for prevalence, costs, and QALY weights that can be used in economic evaluations of interventions directed at DR and as benchmarks for future DR research in order to follow up consequences of changes in diabetes care. In addition, it demonstrates that the choice of method for estimating QALY weights may have an impact on whether an intervention is considered cost-effective.

To investigate the possibility that chronic diabetes mellitus was related to specific neuropsychological deficits, cognitive functioning was measured in subjects with diabetic retinopathy (without secondary disabilities), and in subjects classified as normal blind adults (also without secondary disabilities). The scores for the two groups were then compared.

This study evaluated the direct link between visual perception and related motor output responses during an optic flow stimulation which induced a perception of forward movement, and during a driving task using a simulator. The experiments focussed on the evaluation of two different complications of diabetes, diabetic retinopathy and diabetic peripheral neuropathy (DPN), in order to evaluate the different contributions of both central and peripheral nervous factors in affecting the sensorimotor integration process in diabetes. Study I. The aim was to assess how optic flow processing contributes to the control of posture and whether it requires the predominant activation of cortical networks involved in motion perception or the intervention of subcortical loops. People with retinopathy and people who had undergone laser treatment showed a higher postural instability compared to control subjects. Differing retinal functionality produced different postural strategies. Based on these findings, postural control seems to be a process dependent on perceptual analysis via feed-forward cortical circuits. Study II. The aim was to assess whether diabetes was associated with alterations of visual gaze behaviour and/or neuromuscular impairment that might adversely affect driving performance. The potential for impaired driving performance with diabetes seems to be represented by diminished eye-steering coordination. While proprioception function seems to indicate the potential for improvement, a slower production of strength in the plantar flexor muscles seems not to influence accelerator pedal control during a driving simulation task in people with diabetes (with and without diabetic peripheral neuropathy). These results confirm the role of visual perception and eye movements in guiding human movements during dailylife activities. In particular, we demonstrated the detrimental effects of diabetes and the different contribution of diabetic retinopathy and diabetic peripheral neuropathy in affecting both central and peripheral components of the sensorimotor integration process.

Magister Public Health - MPH
BACKGROUND AND RATIONALE: The Cape Town Metro District Health Service (MDHS) has introduced a Diabetic RetinopathyScreening (DRS) programme incorporating retinal fundal photography in diabetic services at primary health care (PHC) facilities. Hitherto, coverage of the DRS programme has been less than optimal in part due to volumes of diabetic patients attending PHC facilities. The aim of this study was to identify possible sub-groups of patients, attending the Cape Town DRS Programme, who are at most risk of diabetic retinopathy and might be prioritised for early diabetic retinopathy detection and subsequent sight-saving treatment. METHODOLOGY: A case-control study of risk factors for treatment-requiring diabetic retinopathy was conducted. This research sampled participants from the DRS programme provided by the MDHS eye care team to Type II diabetics attending public PHC facilities within the Klipfontein and Mitchells Plain Sub-Districts. Based on fundal images, cases were selected as those requiring ophthalmological treatment; and controls (three matched per case by area of residence) as those judged as not requiring ophthalmological treatment for diabetic retinopathy. Data on possible risk factors (clinical, laboratory) were extracted from the patients' folders. RESULT: The study included 453 participants, of whom 113 (24.9%) were cases and 340 (75.1%) were controls. Three factors were significantly associated with treatment-requiring diabetic retinopathy on multivariate analysis: Insulin dependency (OR of 2.96, 95% CI: 1.75 – 5.00); duration of diabetes of more than 10 years (OR of 3.44, 95% CI: 2.06 – 5.74) and sustained hyperglycaemia over the past six months (OR of 3.73, 95% CI: 1.69 – 8.22). A screening algorithm combining these criteria had a sensitivity of 61.2% (95% CI: 51.9 – 70.5). CONCLUSION: The findings indicate that a sub-set of patients attending the DRS programme in the Klipfontein and Mitchells Plain Sub-Districts have a greater likelihood of presenting with treatment-requiring diabetic retinopathy. Further research is required to develop a tool that is sufficiently sensitive to safely prioritise patients for fundal screening.
National Research Foundation (NRF)

Includes abstract.
Includes bibliographical references.
Objective: To investigate the awareness of diabetic retinopathy (DR) among diabetics in the Cape Town Metropole by assessing: - Whether diabetics know that diabetes can affect their eyes. - Whether the awareness of DR differs according to subtype of diabetes, place of treatment (private versus public sector), level of education and socio-economic status. - Knowledge of systemic risk factors for developing DR. - Knowledge of treatment of DR. A population-based cross-sectional study was conducted as part of the Rapid Assessment of Avoidable Blindness (RAAB) survey undertaken in 2010

La neurodegeneració és un event precoç en la patogènia de la retinopatia diabètica (RD). De fet, recentment la American Diabetes Association ha definit la RD com una complicació neurovascular teixit-específica, emfatitzant així la importància de la unitat neurovascular en el desenvolupament de la RD. La retina és un teixit que deriva del cervell i disposem d’evidència creixent que indica que els diabètics tipus 2 tenen un major risc de desenvolupar malalties neurodegeneratives com la malaltia d’Alzheimer. Així doncs, sembla raonable postular que els mediadors del procés de neurodegeneració que succeeix al cervell també es troben presents a la retina del pacient diabètic. L’objectiu general d’aquesta tesi doctoral és investigar la relació entre la neurodegeneració a la retina i al cervell i les seves potencials implicacions clíniques i terapèutiques. La primera part d’aquesta tesi doctoral es centra en un seguit d’estudis experimentals per tal d’identificar mediadors de la disfunció de la unitat neurovascular. Amb aquest objectiu, s’ha realitzat un estudi “d’hipòtesi lliure” comparant retines humanes de subjectes no diabètics i diabètics amb i sense activació glial (que és una de les principals característiques de la neurodegeneració). Un dels resultats obtinguts ha estat que diverses vies relacionades amb les malalties neurodegeneratives es troben diferencialment expressades en retines de pacients diabètics i especialment en aquells amb activació glial. Aquesta observació recolza el concepte de que existeix un substrat comú entre els processos neurodegeneratius que succeeixen al cervell i a la retina. A més a més, s’ha observat una disminució en la expressió de diverses proteïnes implicades en el transport axonal i del citoesquelet de l’axó a les retines de donants diabètics amb activació glial. Per altra banda, l’activació glial induïda per la diabetis s’associa a una disregulació del sistema del complement, així com a un increment de les proteïnes que governen el citoesquelet de l’endoteli. Aquests resultats s’han validat per mètodes ortogonals. Aquestes troballes contribueixen no només en la comprensió dels mecanismes implicats en l’increment de la permeabilitat vascular induït per la disfunció de la unitat neurovascular, sinó que podrien tenir potencials implicacions terapèutiques. La segona part d’aquesta tesi doctoral, es basa en una “hipòtesi dirigida” i té l’objectiu d’examinar el paper de l’endotelina-1 en la disfunció neurovascular que succeeix en la RD. Això es fonamenta en el fet de que per mitjà dels receptors ETA l’endotelina-1 indueix dany vascular, mentre que a través dels receptors ETB indueix neurodegeneració. En primer lloc, hem detectat un augment en l’expressió de l’endotelina-1 i els seus receptors (tant ETA i ETB) en les retines de donants diabètics en comparació amb donants no diabètics. En segon lloc, hem pogut demostrar que l’aplicació tòpica de bosentan (que bloqueja els receptors ETA i ETB) prevé la neurodegeneració de la retina induïda per la diabetis en el ratolí db/db. A més, entre els efectes del bosentan hi ha la inhibició de l’activació de les vies induïdes per la diabetis PKC-β, TNF-α i VEGF, fet que explica els beneficis a nivell vascular que ofereix aquest tractament. L’efecte beneficiós dual (neurotròpic i vasculotròpic), així com els resultats de l’estudi farmacocinètic, indiquen que el bosentan pot ésser un excel·lent candidat a explorar en futurs assajos clínics. La tercera part de la tesi és un estudi clínic adreçat a reforçar el concepte de que l’avaluació de la neurodegeneració de la retina podria ser una eina útil per identificar aquells pacients diabètics en risc de desenvolupar demència. En aquest sentit, en un estudi previ vam demostrar que la sensibilitat de la retina avaluada per microperimetria es relacionava amb la neurodegeneració a nivell cerebral i podria ésser un biomarcador útil per identificar aquells pacients diabètics tipus 2 en risc de desenvolupar malaltia d’Alzheimer. En aquest treball hem avaluat si l’estudi de la fixació de la mirada, que és un paràmetre que també pot ser avaluat per microperimetria, s’associa al deteriorament cognitiu. En aquest sentit, estudis previs indiquen que la capacitat per mantenir la mirada fixada en una localització es troba alterada en la malaltia d’Alzheimer. Els nostres resultats mostren que la fixació de la mirada és més inestable a mesura que avança l’estat de deteriorament cognitiu. A més a més, l’avaluació dels paràmetres relacionats amb la fixació millora de forma significativa la sensibilitat de la retina com a test diagnòstic per a diferenciar els pacients diabètics amb deteriorament cognitiu incipient dels normocognitius. Així doncs, la mesura de la sensibilitat de la retina en combinació amb els paràmetres relacionats amb la fixació utilitzant la microperimetria podria ser un mètode fiable per a detectar estadis prodròmics de la demència en la població de diabètics tipus 2. Esperem que aquestes troballes esdevinguin la prova de concepte per a la realització d’un estudi clínic de llarga escala. Aquest treball, contribueix al coneixement dels mediadors de la disfunció neurovascular en etapes inicials de la RD i amplia el coneixement del vincle existent entre la neurodegeneració que succeeix al cervell i a la retina en la població afecta de diabetis mellitus tipus 2. A més a més, les nostres troballes suggereixen futurs candidats com a potencials dianes terapèutiques per al tractament de la RD.
Neurodegeneration is an early event in the pathogenesis of diabetic retinopathy (DR). In fact, the American Diabetes Association has recently defined DR as a highly tissue-specific neurovascular complication, thus emphasizing the importance of the neurovascular unit in the development of DR. The retina is a brain-derived tissue and there is growing evidence indicating that type 2 diabetic subjects are more prone to develop neurodegenerative processes such as Alzheimer’s disease. Therefore, it seems reasonable to postulate that the mediators of the neurodegenerative process that occurs in the brain could also be present in the diabetic retina. On this basis, the general objective of this thesis is to investigate the relationship between retinal and brain neurodegeneration and its potential clinical and therapeutic implications. The first part of this thesis focuses on experimental studies addressed to identifying mediators of impairment of the neurovascular unit. For this purpose a proteomic “hypothesis-free” study was performed comparing human retinas from non-diabetic and diabetic donors with and without glial activation (one of the hallmarks of retinal neurodegeneration). The Ingenuity Pathway Analysis revealed that several critical pathways related to brain neurodegenerative diseases were differently expressed in retinas from diabetic patients and in particular in those with glial activation. This observation supports the concept that a common soil exists in the neurodegenerative processes that occur in the retina and the brain. In addition, a downregulation of several proteins involved in axonal transport and the cytoskeleton was found in retinas from diabetic donors with glial activation. Furthermore, diabetes-induced glial activation was associated with a dysregulation of the complement system, as well as an upregulation of the proteins that govern the cytoskeleton changes. These results were confirmed by orthogonal methods. These novel findings contribute not only to our understanding of the mechanisms involved in the vascular leakage induced by neurovascular unit impairment, but could also have potential therapeutic implications. The second part of this doctoral thesis is based on a “driven hypothesis” aimed at examining whether endothelin-1 plays a pivotal role in the neurovascular unit impairment that occurs in DR. This is based on the fact that by means of ETA receptors ET-1 leads to vascular damage and through ETB induces neurodegeneration. We first found an overexpression of both ET-1 and its receptors (ETA and ETB) in the retinas from diabetic donors in comparison with nondiabetic donors. Second, we found that topical administration of bosentan (a blocker of ETA and ETB receptors) prevented retinal neurodegeneration induced by diabetes in the db/db mouse model. In addition, the inhibition of diabetes-induced upregulation of PKC-β, TNF-α and VEGF plays an important role in the beneficial vascular action of bosentan. These dual beneficial effects of bosentan (neurotrophic and vasculotropic) and the pharmacokinetic results point to this drug as an excellent candidate to be tested in clinical trials. The third part of the thesis is a clinical study addressed to reinforcing the concept that the assessment of retinal neurodegeneration could be a useful tool to identify those diabetic subjects at risk of developing dementia. Indeed, in a previous study we demonstrated that retinal sensitivity assessed by fundus-driven microperimetry was related to brain neurodegeneration and could be a useful biomarker for identifying patients with T2D who are at risk of developing Alzheimer’s disease. In the present work, we assessed whether gaze fixation, a parameter that can also be assessed by retinal microperimetry, is associated with cognitive impairment. This is based on previous evidence indicating that the capacity to maintain visual gaze on a single location (fixation) is hampered in Alzheimer’s disease. Our results showed that gaze fixation is more unstable as cognitive impairment progresses. Moreover the assessment of fixational parameters significantly improves retinal sensitivity assessment in differentiating those subjects with mild cognitive impairment from normocognitive diabetic subjects. Therefore, the measurement of retinal sensitivity in combination with parameters of fixation by using microperimetry could be a reliable method for detecting prodromal stages of dementia in the T2D population. Hopefully, these findings will be the proof of concept of a large scale-clinical study. Overall, this work contributes to the knowledge of the mediators of neurovascular unit impairment in the early stages of DR and increases our understanding of the link between retinal and brain neurodegeneration in the setting of the type 2 diabetic population. In addition, our findings suggest further candidates as new potential targets for the treatment of DR.

Diabetic retinopathy (DR) is the most common microvascular complication of diabetes and a leading cause of blindness. Increased vascular permeability in the retina following blood-retinal barrier (BRB) breakdown is a clinically significant event and a major cause of vision loss. VEGF blockade, despite being the only treatment to improve visual acuity, has a limited effectiveness for a majority of patients. A significant proportion of patients develop resistance to treatment, which implies that other factors are also involved in the pathology of this disease. There is currently a major unmet clinical need for therapeutics which target the early stages of DR prior to the onset of overt vascular symptoms. The aim of this thesis was to investigate early diabetes-induced changes to the retina and their effects on the vasculature, in order to identify novel potential therapeutic targets. This was achieved by investigating the effects of high glucose and glycated albumin on the vasculature using the mouse metatarsal assay, an ex vivo model of angiogenesis and the effects of diabetes on the retina with the streptozotocin-induced diabetic mouse. Both high glucose and glycated albumin altered angiogenesis in the metatarsal assay. Investigation of the diabetic mouse retina revealed evidence of increased inflammation and oxidative stress at the cellular and molecular level, accompanied with evidence of vascular leakage. qPCR analysis revealed an increase in Angptl6 and Lrg1 expression of which had not been investigated in the diabetic mouse retina before. Studies with transgenic mouse models implied that Lrg1 is involved in the early stages of pathophysiology of DR and may be a suitable therapeutic target prior to the onset of overt vascular symptoms.

Diabetic retinopathy is a microvascular complication of type 1 and type 2 diabetes, affecting the retinal vasculature of the eye. In the Scottish diabetic retinopathy grading scheme (version 1.1), the severity of diabetic retinopathy is classified as no retinopathy, mild background, observable background, severe non-proliferative and proliferative retinopathy. In the GoDARTS (Genetics of Diabetes Audit and Research Tayside) cohort, we have longitudinal data of retinopathy in diabetic patients since 1990. 3,734 and 3,673 GoDARTS patients were genotyped in the Affymetrix Genome-wide Human SNP Array 6.0 and Illumina HumanOmniExpress BeadChip, respectively. As the pathophysiology of diabetic retinopathy remains elusive, the aim of this thesis is to use the GoDARTS phenotype and genotype data to study clinical and genetic determinants for diabetic retinopathy.

Diabetic retinopathy (DR) is a chronic, progressive and possibly vision-threatening eye disease. Early detection and diagnosis of DR, prior to the development of any lesions, is paramount for more efficiently dealing with it and managing its consequences. This thesis investigates and proposes a number of candidate geometric and haemodynamic biomarkers, derived from fundus images of the retinal vasculature, which can be reliably utilised for identifying the progression from diabetes to DR. Numerous studies exist in literature that investigate only some of these biomarkers in independent normal, diabetic and DR cohorts. However, none exist, to the best of my knowledge, that investigates more than 100 biomarkers altogether, both geometric and haemodynamic ones, for identifying the progression to DR, by also using a novel experimental design, where the same exact matched junctions and subjects are evaluated in a four year period that includes the last three years pre-DR (still diabetic eye) and the onset of DR (progressors’ group). Multiple additional conventional experimental designs, such as non-matched junctions, non-progressors’ group, and a combination of them are also adopted in order to present the superiority of this type of analysis for retinal features. Therefore, this thesis aims to present a complete framework and some novel knowledge, based on statistical analysis, feature selection processes and classification models, so as to provide robust, rigorous and meaningful statistical inferences, alongside efficient feature subsets that can identify the stages of the progression. In addition, a new and improved method for more accurately summarising the calibres of the retinal vessel trunks is also presented. The first original contribution of this thesis is that a series of haemodynamic features (blood flow rate, blood flow velocity, etc.), which are estimated from the retinal vascular geometry based on some boundary conditions, are applied to studying the progression from diabetes to DR. These features are found to undoubtedly contribute to the inferences and the understanding of the progression, yielding significant results, mainly for the venular network. The second major contribution is the proposed framework and the experimental design for more accurately and efficiently studying and quantifying the vascular alterations that occur during the progression to DR and that can be safely attributed only to this progression. The combination of the framework and the experimental design lead to more sound and concrete inferences, providing a set of features, such as the central retinal artery and vein equivalent, fractal dimension, blood flow rate, etc., that are indeed biomarkers of progression to DR. The third major contribution of this work is the new and improved method for more accurately summarising the calibre of an arterial or venular trunk, with a direct application to estimating the central retinal artery equivalent (CRAE), the central retinal vein equivalent (CRVE) and their quotient, the arteriovenous ratio (AVR). Finally, the improved method is shown to truly make a notable difference in the estimations, when compared to the established alternative method in literature, with an improvement between 0.24% and 0.49% in terms of the mean absolute percentage error and 0.013 in the area under the curve. I have demonstrated that some thoroughly planned experimental studies based on a comprehensive framework, which combines image processing algorithms, statistical and classification models, feature selection processes, and robust haemodynamic and geometric features, extracted from the retinal vasculature (as a whole and from specific areas of interest), provide altogether succinct evidence that the early detection of the progression from diabetes to DR can be indeed achieved. The performance that the eight different classification combinations achieved in terms of the area under the curve varied from 0.745 to 0.968.

Thesis (M.A.) PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you.
Diabetes is a disease characterized by high blood glucose levels that result from a defect in the body’s inability to produce or utilize insulin. This disease increases the risk of long-term health problems and affects multiple organ systems; one complication being diabetic retinopathy (DR) that causes changes in the blood vessels of the retina. Diabetic retinopathy is the leading cause of blindness in the working age population. Early events in the pathogenesis of diabetic retinopathy are characterized by retinal vascular cell loss and excess retinal capillary leakage. Studies have shown that the retinal vascular cell loss occurs by programmed cell death while excess permeability develops at least in part through compromised tight junctions. Studies, including those from our laboratory, have also established that high glucose or diabetes reduces a specific protein, Cx43, found in intercellular communication channels or gap junctions, and contributes to the development of programmed cell death. It is currently unknown if there is an association between high glucose- or diabetes-induced Cx43 downregulation and excess permeability. Importantly, previous studies have shown that reduced Cx43 can promote excess permeability, but the mechanism underlying this phenomenon is not well understood. In this study, the effects of reduced Cx43 expression on proteins involved in cell-cell adhesion, or tight junctions, was examined. Specifically, experimentally induced Cx43 downregulation by a gene silencing technique affected the expression of tight junction proteins (ZO-1, occludin, claudin-5) in rat retinal endothelial cells. ZO-1 and occludin protein levels were decreased while claudin-5 levels were increased. In addition, permeability was increased when Cx43 was downregulated. These observations suggest that expression levels of Cx43 regulate barrier characteristics by influencing the expression of tight junction proteins. Findings from this study provide an insight into how high glucose-induced Cx43 downregulation compromises endothelial barrier characteristics through modulation of tight junction proteins.
2031-01-01

Aims The early recognition of diabetic retinopathy is critical in preventing visual morbidity and mortality. The aims were: • To examine the attitudes of General Practitioners (GPs) towards diabetic retinopathy (DR) screening in primary care. • To evaluate an algorithm for detecting DR developed by the Commonwealth Scientific and Industrial Research Organisation (CSIRO). • To evaluate the algorithm against two different ophthalmologist graders. • To evaluate the performance effect of re-training the algorithm. Methods • A qualitative analysis of interviews with 15 GPs in Australia. • Non mydriatic fundus photographs of participants in the LANDMark study, with and without diabetes, were graded and compared with the automated gradings of the CSIRO’s algorithm, after which the algorithm was re-trained and performance re- analysed. Results • 15 GPs aged 54.7±15.5 years completed interviews. None of the participants reported performing DR screening in their general practices. Seven themes were identified as key areas for the successful introduction of DR screening into wider practice. • The sensitivity of the CSIRO’s algorithm in detecting referable DR was 53.1%, 74.1% and 73.1% as compared with the first grader, the second grader, and where both graders agreed, respectively. The sensitivity of the re-trained algorithm was 59.4%, 85.2% and 84.6% as compared with the first grader, the second grader and where both graders agreed, respectively. Conclusion • This study identified specific strategies to enable the wider implementation of DR screening in general practice and to inform policymakers in developing a better framework for DR screening in primary care. • The measured performance of the algorithm depended on the reference standard used, and re-training the algorithm improved its performance. Grader variability, intrinsic errors within an algorithm’s ‘black box’ and good study design are all factors that can affect measured performance of an algorithm.

Background: Diabetes Mellitus is an emerging public health problem in Africa. Evidence suggests that globalization, rapid urbanization and a nutritional transition have led to the rise in the prevalence of diabetes mellitus in Africa. Diabetic retinopathy is a common complication of diabetes mellitus that causes visual impairment and subsequent blindness. Early detection and prompt treatment can prevent blindness in up to 90% of patients. The common risk factors for diabetic retinopathy include hypertension, hyperglycemia and long duration of diabetes. Other risk factors include obesity, hyperlipidemia, smoking, puberty and pregnancy. There is limited data on diabetic retinopathy and its associated risk factors in Zambia. An understanding of these factors would help in the effective management of diabetic retinopathy. Methods: A secondary data analysis of data obtained from a hospital-based cross-sectional study of diabetic patients attending diabetic clinics in the Copperbelt Province in Zambia was carried out. All diabetic patients that attended the retinopathy-screening program between April 2012 and September 2012 were eligible for the primary study. The secondary data analysis was restricted to patients 18 years and older. Data analysis was carried out by R version 3.3.1. The characteristics of the study population were summarized using descriptive statistics. Univariate logistic regression analysis was used to select potential candidates for the multivariate regression model at p-value cutoff point ≤ 0.25 and variables of known clinical relevance were also included in the multivariable analysis. The final model fitness was checked using Hosmer and Lemeshow chi-square test. Finally, statistical significance was tested at P-value <0.05. Results: The prevalence of diabetic retinopathy was 19.4%. Multivariate analysis showed that the odds of diabetic retinopathy were significantly associated with age (OR =1.05: 95%Cl; 1.03-1.06), duration (OR=1.39: 95%Cl; 1.27-1.52), weight (OR =0.98: 95%Cl; 0.97-0.98), blood glucose (OR =1.04: 95Cl; 1.02-1.07) and systolic blood pressure (OR = 1.01: 95Cl; 1.00-1.02). Conclusion: Duration of diabetes, age, systolic blood pressure, weight and blood glucose levels were significantly associated with diabetic retinopathy in this study. More comprehensive population screening strategies and treatment programs addressing these risk factors should be put in place.

One of the most significant complications of diabetes is retinopathy. Diabetic retinopathy (DR), a chronic progressive sight-threatening disease of the retinal microvasculature, is the leading cause of treatable blindness in the working age group. Another emerging complication of diabetes is cognitive impairment (Cl). The exact link between diabetes and Cl remains elusive. One theory is that microvascular changes in the brain may be responsible for change in cognition in diabetes. In this study, it was hypothesised that increased severity of DR was associated with impaired cognition (cerebro-microvascular disease) in individuals with Type 2 Diabetes (T2DM). 381 men and women with T2DM recruited to the South East London Diabetic Retinopathy Study were stratified by severity of DR (no/mild retinopathy and proliferative diabetic retinopathy (PDR)) and severity of diabetic maculopathy (non-clinically significant macular oedema (non-CSMO) and CSMO). Each subject underwent tests of cognitive function, psychosocial assessment, ophthalmic and physical examination. Bivariate analysis between categories of DR and maculopathy (ANOVA, Chi square) and ANCOVA for the cognitive scores by DR severity were conducted using SPSS v17. Severity of DR demonstrated an inverse relationship with Cl in patients with T2DM (fully adjusted model). No association was found between severity of maculopathy and Cl. Retinal arteriolar and venular dilation was associated with lower cognition scores in patients with no/mild retinopathy. Decreased levels of serum factor Apo A was associated with decreased cognition. Participants with Cl had consistently elevated risk of stroke compared to participants with no Cl, irrespective of their DR status. Cognition scores also varied by ethnic grouping; participants of ethnic minorities had significantly lower cognition scores than Caucasian participants.

In recognition of the increasing prevalence of diabetes in Brunei, and the expected increase in diabetic retinopathy (DR), primary health centre based DR screening was introduced in 2006 for seven health centres in the Brunei-Muara district. The Brunei National Prevention of Blindness from Diabetic Retinopathy is a policy document calling for DR screening to be made systematic at a national level. However, the effectiveness of the model in practice was not evaluated and the DR screening programme was launched without a baseline survey and situation assessment. Consequently, the responsiveness of the health system to embed a systematic approach to DR screening has faced many constraints and was slow to evolve. This study has provided evidence to support the implementation of the policy document and baseline information on the gaps and challenges within the key service provision stages for DR screening and treatment. The overall objective of this thesis was to evaluate the DR screening model in the Brunei-Muara District. Results from this study suggest that the DR screening model in Brunei-Muara is partially systematic. The main findings showed that key processes are in place at different stages of DR screening and treatment and that sufficient resources have been allocated to detect sight threatening diabetic retinopathy (STDR) at primary health centres (PHCs) and to treat STDR at the national eye centre (NEC). This was supported by the good DR annual screening uptake rates (77%) and low DR prevalence rates (5.8%) reported in this study. However, the lack of monitoring of both the implementation processes and screening effectiveness was viewed as key limitations in the programme. This was evident through process gaps observed throughout the DR screening and treatment pathway including the identification of patients for screening at PHCs, GP to DR referral process, referral for treatment processes to NEC and disease registers that were not integrated and lacked accuracy. This was also backed by evidence that DR screening coverage rates were low (56%) across all health centres. Based on a generic framework to analyse development of DR screening programmes used in this study, the existing screening model could be enhanced by improving screening coverage rates, universal access to DR treatment, trained and certified workforce, implementation of a call and recall system and systematic digital photography screening system. However, further studies are required before these recommendations could be implemented.

A two-stage qualitative research strategy using semi-structured interviews was conducted with a convenience sample of 45 participants who lives with type 2 diabetes. In Stage One of the research, a qualitative study was conducted using semi-structured interviews with a purposive sample of 25 participants. Of these, 20 participants were diagnosed with type 2 diabetes, two participants were primary care physicians, two were ophthalmologists, and one was a retinal screener. People with diabetes were purposely recruited to fall into four groups with different grades of diabetic retinopathy. The aim of Stage One was to explore how people with type 2 diabetes perceive diabetic retinopathy risk, their understanding of risk information, and to appraise existing risk communication tools that have been used in other clinical settings. The data from Stage One was analysed and used to develop a risk communication tool designed to provide risk information about diabetic retinopathy and diabetic screening results to people with type 2 diabetes, which was then used in Stage Two. In Stage Two of this research, a total of twenty people with type 2 diabetes were recruited. Participants were divided into two groups based on their grade of diabetic retinopathy. Group one: 10 participants with no diabetic retinopathy (R0); Group two: 10 participants who had background diabetic retinopathy (R1). The aim of Stage Two was to i) appraise a newly developed risk communication tool that was developed to communicate risk information about diabetic retinopathy to people with type 2 diabetes, ii) to explore the influence of the new developed risk tool on risk perception and on diabetes self-care management, and iii) to establish a method(s) by which risk information about diabetic retinopathy can be effectively communicated to people with type 2 diabetes. All interviews were audio recorded and transcribed using a digital recording machine. Data was analysed using constructivist grounded theory approach.

La retinopatia diabètica (DR) és una malaltia crònica. És una de les principals complicacions de diabetis i una causa essencial de pèrdua de visió entre les persones que pateixen diabetis. Els pacients diabètics han de ser analitzats periòdicament per tal de detectar signes de desenvolupament de la retinopatia en una fase inicial. El cribratge precoç i freqüent disminueix el risc de pèrdua de visió i minimitza la càrrega als centres assistencials. El nombre dels pacients diabètics està en augment i creixements ràpids, de manera que el fa difícil que consumeix recursos per realitzar un cribatge anual a tots ells. L’objectiu principal d’aquest doctorat. la tesi consisteix en construir un sistema de suport de decisions clíniques (CDSS) basat en dades de registre de salut electrònic (EHR). S'utilitzarà aquest CDSS per estimar el risc de desenvolupar RD. En aquesta tesi doctoral s'estudien mètodes d'aprenentatge automàtic per constuir un CDSS basat en regles lingüístiques difuses. El coneixement expressat en aquest tipus de regles facilita que el metge sàpiga quines combindacions de les condicions són les poden provocar el risc de desenvolupar RD. En aquest treball, proposo un mètode per reduir la incertesa en la classificació dels pacients que utilitzen arbres de decisió difusos (FDT). A continuació es combinen diferents arbres, usant la tècnica de Fuzzy Random Forest per millorar la qualitat de la predicció. A continuació es proposen diverses tècniques d'agregació que millorin la fusió dels resultats que ens dóna cadascun dels arbres FDT. Per millorar la decisió final dels nostres models, proposo tres mesures difuses que s'utilitzen amb integrals de Choquet i Sugeno. La definició d’aquestes mesures difuses es basa en els valors de confiança de les regles. En particular, una d'elles és una mesura difusa que es troba en la qual l'estructura jeràrquica de la FDT és explotada per trobar els valors de la mesura difusa. El resultat final de la recerca feta ha donat lloc a un programari que es pot instal·lar en centres d’assistència primària i hospitals, i pot ser usat pels metges de capçalera per fer l'avaluació preventiva i el cribatge de la Retinopatia Diabètica.
La retinopatía diabética (RD) es una enfermedad crónica. Es una de las principales complicaciones de diabetes y una causa esencial de pérdida de visión entre las personas que padecen diabetes. Los pacientes diabéticos deben ser examinados periódicamente para detectar signos de diabetes. desarrollo de retinopatía en una etapa temprana. La detección temprana y frecuente disminuye el riesgo de pérdida de visión y minimiza la carga en los centros de salud. El número de pacientes diabéticos es enorme y está aumentando rápidamente, lo que lo hace difícil y Consume recursos para realizar una evaluación anual para todos ellos. El objetivo principal de esta tesis es construir un sistema de apoyo a la decisión clínica (CDSS) basado en datos de registros de salud electrónicos (EHR). Este CDSS será utilizado para estimar el riesgo de desarrollar RD. En este tesis doctoral se estudian métodos de aprendizaje automático para construir un CDSS basado en reglas lingüísticas difusas. El conocimiento expresado en este tipo de reglas facilita que el médico pueda saber que combinaciones de las condiciones son las que pueden provocar el riesgo de desarrollar RD. En este trabajo propongo un método para reducir la incertidumbre en la clasificación de los pacientes que usan árboles de decisión difusos (FDT). A continuación se combinan diferentes árboles usando la técnica de Fuzzy Random Forest para mejorar la calidad de la predicción. Se proponen también varias políticas para fusionar los resultados de que nos da cada uno de los árboles (FDT). Para mejorar la decisión final propongo tres medidas difusas que se usan con las integrales Choquet y Sugeno. La definición de estas medidas difusas se basa en los valores de confianza de las reglas. En particular, uno de ellos es una medida difusa descomponible en la que se usa la estructura jerárquica del FDT para encontrar los valores de la medida difusa. Como resultado final de la investigación se ha construido un software que puede instalarse en centros de atención médica y hospitales, i que puede ser usado por los médicos de cabecera para hacer la evaluación preventiva y el cribado de la Retinopatía Diabética.
Diabetic retinopathy (DR) is a chronic illness. It is one of the main complications of diabetes, and an essential cause of vision loss among people suffering from diabetes. Diabetic patients must be periodically screened in order to detect signs of diabetic retinopathy development in an early stage. Early and frequent screening decreases the risk of vision loss and minimizes the load on the health care centres. The number of the diabetic patients is huge and rapidly increasing so that makes it hard and resource-consuming to perform a yearly screening to all of them. The main goal of this Ph.D. thesis is to build a clinical decision support system (CDSS) based on electronic health record (EHR) data. This CDSS will be utilised to estimate the risk of developing RD. In this Ph.D. thesis, I focus on developing novel interpretable machine learning systems. Fuzzy based systems with linguistic terms are going to be proposed. The output of such systems makes the physician know what combinations of the features that can cause the risk of developing DR. In this work, I propose a method to reduce the uncertainty in classifying diabetic patients using fuzzy decision trees. A Fuzzy Random forest (FRF) approach is proposed as well to estimate the risk for developing DR. Several policies are going to be proposed to merge the classification results achieved by different Fuzzy Decision Trees (FDT) models to improve the quality of the final decision of our models, I propose three fuzzy measures that are used with Choquet and Sugeno integrals. The definition of these fuzzy measures is based on the confidence values of the rules. In particular, one of them is a decomposable fuzzy measure in which the hierarchical structure of the FDT is exploited to find the values of the fuzzy measure. Out of this Ph.D. work, we have built a CDSS software that may be installed in the health care centres and hospitals in order to evaluate and detect Diabetic Retinopathy at early stages.

L’objectiu general d’aquesta tesi doctoral va ser desenvolupar, analitzar i validar noves eines bioinformàtiques que converteixin les dades crues de metabolòmica (adquirides per espectrometria de masses) en coneixement biològic amb la finalitat d’estudiar les alteracions en el proteoma i metaboloma de cèl·lules humanes del pigment retinal exposades a condicions de hiperglucèmia i/o hipòxia. Per assolir aquest objectiu general, aquesta tesi s'ha estructurat en dos blocs principals: ⁻ Objectius metodològics: (i) Hem analitzat les bases de dades espectrals de masses de metabolòmica basades en LC / MS. (ii) Finalment, hem generat i millorat la caracterització de les dades de metabolómica de LC / MS centrant-nos en l'anotació de MS1 i MS2. ⁻ Objectius biològics: (iii) Hem proposat un nou mètode que detecta i analitza els canvis en les xarxes d'interacció proteïna-proteïna (PPI) per condicions d’hiperglucèmia i / o hipòxia. (iv) Hem presentat un flux de treball nou que és capaç de predir i validar les alteracions metabòliques degudes a condicions d’hiperglucèmia i / o hipòxia integrant a la vegada les dades d'expressió de proteïnes en les xarxes metabòliques.
El objetivo general de esta tesis doctoral fue desarrollar, analizar y validar nuevas herramientas bioinformáticas que conviertan los datos crudos de metabolómica (adquiridos por espectrometría de masas) en conocimiento biológico con el fin de estudiar las alteraciones en el proteoma y metaboloma de células humanas del pigmento retinal expuestas a condiciones de hiperglucemia y / o hipoxia. ⁻ Objetivos metodológicos: (i) Hemos analizado las bases de datos espectrales de masas de metabolómica basada en LC / MS. (ii) Finalmente, hemos generado y mejorado la caracterización de los datos de metabolómica de LC / MS centrándonos en la anotación de MS1 y MS2. ⁻ Objetivos biológicos: (iii) Hemos propuesto un nuevo método que detecta y analiza los cambios en las redes de interacción proteína-proteína (PPI) por condiciones hiperglucemia y / o hipoxia. (iv) Hemos presentado un flujo de trabajo novedoso que es capaz de predecir y validar las alteraciones metabólicas debidas a condiciones hiperglucemia y / o hipoxia integrando a la vez los datos de expresión de proteínas en las redes metabólicas.
The general objective of this doctoral thesis was to develop, analyse and validate new bioinformatic tools for converting raw MS-based metabolomics data into biological knowledge, in order to study alterations in the proteome and metabolome of human retinal pigment epithelium cells exposed to hyperglycemic and/or hypoxic conditions. To reach this general objective, this thesis has been structured in two main blocks: ⁻ Methodological aims: (i) We have analysed mass spectral databases for LC/MS-based untargeted metabolomics. (ii) Finally, we have generated and improved the characterization of LC/MS metabolomics data focusing on MS1 and MS2 annotation. ⁻ Biological aims: (iii) We have proposed a novel method that detects and analyses changes in protein-protein interaction (PPI) networks by hyperglycemic and/or hypoxic conditions. (iv) We have presented a novel workflow which is able to predict and validate metabolite alterations due to hyperglycemic and/or hypoxic conditions integrating protein expression data in metabolic networks.

Background: Screening for diabetic retinopathy (DR) has been proven effective and cost-effective in preventing blindness. Hong Kong (HK) has a mixed health care economy and, before this study, there was no systematic screening for DR. The optimal screening interval for DR screening is controversial with some countries extending it to 2 or more years. Risk algorithms tailor screening intervals to an individual but the safety of a 2-year interval and the validity of the Iceland Risk Algorithm (IRA) are uncertain in HK. This study assesses the impact of charging a co-payment for DR screening in the public sector, evaluates its cost-effectiveness and examines the use of an algorithm to determine optimal screening intervals for subjects in HK. Methods: A randomized controlled trial (RCT) was conducted with subjects with diabetes from two general outpatient public clinics randomized to free screening or pay screening with a co-payment of HK$60. Cost-effectiveness analysis used a Markov cohort model to compare these with opportunistic screening. Incremental cost-effectiveness ratios (ICERs) were calculated and one way and probabilistic sensitivity performed. Subjects were followed up for two years to examine the safety of a 2-year screening interval and to test the validity of the IRA in predicting sight threatening diabetic retinopathy (STDR). A new prediction model using cohort data was developed using logistic regression and tested in a similar fashion. Results: After randomization, 1316 in the free and 1277 in the pay group agreed to participate. Uptake of screening was 88.5% (1165/1316) and 82.4% (1052/1277) in free and pay groups respectively (Pearson chi=19.74, P<0.001). Being in the pay group was associated with lower uptake of screening (OR=0.59, 0.47 to 0.74) and lower detection rates of DR (OR=0.73, 0.60 to 0.90) after adjustment. From the societal perspective, pay systematic DR screening rather than opportunistic screening gives an ICER of HK$94,630/QALY gained. Free rather than pay systematic screening, had an ICER of HK$199,741/QALY gained. Probabilistic sensitivity analysis showed when willingness to pay for a QALY was HK$186,186 or more, free systematic screening had the highest probability of being cost-effective. The 2-year cumulative incidence of STDR was low for those with no DR (2.9%) and those who developed STDR did not experience severe visual loss during follow up. The IRA had good discrimination for identifying STDR, but significantly lacked calibration. The new prediction model improved discrimination and calibration compared with the IRA. Conclusion: A number of people in the pay group did not uptake screening and appear to be higher risk cases. The inverse care law appears to operate even with this relatively small co-payment. From the societal perspective, free systematic screening was more cost-effective than pay within the WHO threshold of 1 x annual per capita GDP (HK$338,520) for a QALY. Free systematic screening can be considered the most cost-effective screening strategy from the societal perspective. We could tailor screening intervals according to individual risks using a new prediction model which appears safe and efficient but which requires further testing with follow-up data.
published_or_final_version
Public Health
Doctoral
Doctor of Philosophy

La Retinopatía Diabética (RD) es la complicación más común de la diabetes y una de las principales causas de ceguera. La RD se ha considerado clásicamente como una enfermedad microcirculatoria de la retina. No obstante, antes de que las anormalidades microcirculatorias se puedan detectar en un examen oftalmoscópico, la neurodegeneración ya está presente. Esto significa que la neurodegeneración es un acontecimiento temprano en la patogenia de la RD. Por tanto, existe la necesidad de tener buenos modelos animales donde se puedan testar fármacos potencialmente neuroprotectores y entender sus mecanismos de acción. En el primer capítulo de la tesis el objetivo fue caracterizar los acontecimientos secuenciales que tienen lugar en la neurodegeneración retiniana en un modelo murino de diabetes tipo 2, el ratón db/db. Se encontró un incremento progresivo con la edad de los marcadores de neurodegeneración (activación glial y apoptosis) en todas las etapas estudiadas. Se observaron anormalidades electroretinográficas en ratones de 16 y 24 pero no a 8 semanas de edad. Además, se observó una acumulación progresiva de glutamato en ratones diabéticos asociada con la disminución de su transportador GLAST. Todas estas anormalidades fueron abolidas al reducir los niveles de glucosa en sangre. Finalmente, a 8 semanas de edad, se encontraron alteraciones en la expresión de varios genes relacionados con la neurotransmisión y el estrés oxidativo como por ejemplo UCP2. Estos resultados sugieren que el ratón db/db reproduce las características del proceso neurodegenerativo que tiene lugar en el ojo diabético humano. Por tanto éste es un modelo apropiado para investigar los mecanismos subyacentes de la neurodegeneración retiniana inducida por la diabetes y para testar fármacos neuroprotectores. En el segundo capítulo se evalúan los efectos potenciales del ácido fenofíbrico (el metabolito activo del fenofibrato) en la prevención de la neurodegeneración retiniana que presenta el ratón db/db. El tratamiento oral durante una semana resultó en la reducción de la activación glial y de la apoptosis en comparación con los ratones tratados con vehículo. Las anormalidades funcionales mejoraron y el tratamiento con ácido fenofíbrico también previno la disminución de GLAST producida por la diabetes. Estos resultados sugieren que la neuroprotección es uno de los mecanismos subyacentes por los cuales el ácido fenofíbrico ejerce sus acciones beneficiosas en la retinopatía diabética. El tercer capítulo se centra en GLP-1 y sus efectos neuroprotectores en la retina. Se ha demostrado que GLP-1 ejerce efectos neuroprotecotres en el sistema nervioso central. El objetivo fue examinar la expresión y contenido de GLP-1R en retinas humanas y de ratón db/db, determinar los efectos neuroprotectores en la retina después de un tratamiento sistémico y otro tópico ocular (colirio) y examinar los mecanismos neuroprotectores subyacentes. Se encontró abundante expresión de GLP-1R en las retinas humanas y de ratón db/db. Además, se demostró que la administración sistémica de agonistas de GLP-1R (liraglutide) previene la neurodegeneración en la retina (activación glial, apoptosis neuronal y anormalidades electroretinográficas). Este efecto puede ser atribuido a una reducción significativa de glutamato extracelular y a un incremento de las vías de señalización pro-supervivencia. Se encontró un nivel similar de neuroprotección usando administración tópica ocular de GLP-1 nativo y de otros agonistas de GLP-1R (liraglutide, lixisenatide y exenatide). Cabe destacar que esta acción neuroprotectora fue observada sin reducción en los niveles de glucosa en sangre. Estos resultados sugieren que la activación de GLP-1R por si misma previene la neurodegeneración en la retina inducida por la diabetes.
Diabetic retinopathy (DR) is the most common complication of diabetes and one of the leading causes of preventable blindness. DR has been classically considered to be a microcirculatory disease of the retina. However, before any microcirculatory abnormalities can be detected under ophthalmoscopic examination, retinal neurodegeneration is already present. This is to say that retinal neurodegeneration is an early event in the pathogenesis of diabetic retinopathy. There is a need to have a good animal model where potentially neuroprotective drugs could be tested on and understand their mechanisms of action. In the first chapter of this thesis the main aim was to characterize the sequential events that take place in retinal neurodegeneration in a murine model of spontaneous type 2 diabetes, the db/db mouse. We found progressively increased levels of the histological markers of neurodegeneration (glial activation and apoptosis) at all stages studied worsening with age. Significant electroretinographic abnormalities were present in diabetic mice at weeks 16 and 24 but not at week 8. Moreover it was observed a progressive accumulation of glutamate in diabetic mice associated with an early downregulation of its transporter GLAST. All this abnormalities were abrogated by lowering blood glucose levels. Finally, a dysregulation of several genes related to neurotransmission and oxidative stress such as UCP2 were found at week 8. All these results suggest that db/db mouse reproduce the features of the neurodegenerative process that occurs in the human diabetic eye. Therefore it is an appropriate model for investigating the underlying mechanisms of diabetes induced retinal neurodegeneration and for testing neuroprotective drugs. In the second chapter the potential effects of fenofibric acid (FA) (the active metabolite of fenofibrate) in preventing retinal neurodegeneration in the db/db mouse are evaluated. Oral treatment for one week resulted in a reduction of glial activation and apoptosis in comparison to vehicle-treated mice. Functional abnormalities were ameliorated and FA treatment also prevented GLAST downregulation induced by diabetes. Our results suggest that neuroprotection is one of the underlying mechanisms by which FA exerts its beneficial actions in diabetic retinopathy. The third chapter is focused on GLP-1 and its neuroprotective effects in the retina. GLP-1 has been demonstrated to have neuroprotective effects in the central nervous system. We sought to examine the expression and content of GLP-1R in human and db/db mice retinas, to determine the retinal neuroprotective effects of systemic and topical administration of GLP-1R agonists in db/db mice and, to examine the underlying neuroprotective mechanisms. We found abundant expression of GLP-1R in the human retina and retinas from db/db mice. Moreover, it has been demonstrated that systemic administration of GLP-1R agonists (liraglutide) prevents retinal neurodegeneration (glial activation, neural apoptosis and electroretinographical abnormalities). This effect can be attributed to a significant reduction of extracellular glutamate and to an increase of prosurvival signalling pathways. We have found a similar neuroprotective effect using topical administration of native GLP-1 and several GLP-1R agonists (liraglutide, lixisenatide and exenatide). Notably, this neuroprotective action was observed without any reduction in blood glucose levels. These results suggest that GLP-1R activation itself prevents diabetes induced retinal neurodegeneration.

The work for this thesis has been carried out in the Diabetic Clinic, Woolmanhill, the Eye Clinic, Foresterhill and the Departments of Bio-Medical Physics and Ophthalmology, University of Aberdeen. One hundred and twenty two patients with type 1 diabetes mellitus were recruited from the Diabetic Clinic, Woolmanhill, and attended a Research Clinic at the Eye Clinic, Foresterhill, on a three monthly basis for two years each between 1992 and 1995. Data was extensively collated relating to diabetic control and diabetic complications. Concentrations and activities of several serum factors were studied in an attempt to elucidate pathogenetic mechanisms in diabetic retinopathy. Serum levels of soluble leucocyte endothelial adhesion molecules were measured to see if there is indirect evidence for increase leucocyte adhesion in diabetic retinopathy. Similar studies were also performed looking at serum induced retinal endothelial capillary cell migration, a putative early feature in the development of sight-threatening new vessel formation. Computer image analysis methods, developed in the Department of Bio-Medical Physics, were modified and evaluated, leading to robust techniques suitable for quantifying lesions of diabetic retinopathy in large numbers of unselected fundal photographs and fluorescein angiograms. This latter work was completed in 1997. As it is known that essential fatty acid metabolism in diabetes is abnormal, leading to low levels of gamma-linolenic acid and its metabolites, the above techniques were used to assess the progress of diabetic retinopathy in a two year crossover trial of dietary gamma-linolenic acid supplementation.

The problem of scalable image recognition has long been a research issue in the area of computer vision. This thesis aims to address this by providing a holistic solution in which ensembles of very large number of classifiers for various image content are initially developed in order to cover as many perspectives of problem space as possible. The selection of these classifiers is then optimised simultaneously using evolutionary algorithms to ensure that the features and classifiers selected are optimal for the heterogeneous system components. To model image context, Hidden Markov Models are established through various evolutionary computation processes. Especially a hybrid evolutionary approach has been developed to find the most suitable contextual models which concurrently guide the searching for optimal classifiers. Finally information from optimised classifiers and context models are fused together to reason and determine the overall image content. This proposed architecture has been tested on Diabetic Retinopathy (DR) image datasets, which exhibit great variability and diversity. Based on the proposed solution, the system is able to recognise the key DR signs and ultimately, to separate normal and abnormal diabetic retinopathy images. Through evolutionary computation, the various components of the system outperformed classical approaches. This is demonstrated through the comparison between combined optimal classifiers and those obtained through traditional combination strategies such as average, sum and majority vote. Experiments also show that hybrid evolutionary approaches for optimising the classifier combination strategy and context models simultaneously perform best, if each component is treated individually. Using the integrated approach, the system developed is capable of separating normal and abnormal retina image with a Sensitivity of 95% and a Specificity of 92%. Among all images the system recognises as normal, 91% are true normal ones

Thesis (M.A.)--Boston University PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you.
Purpose: The goal of this study is to test the hypothesis that high glucose, a prevalent characteristic of diabetes, induces vascular cell death associated with diabetic retinopathy by compromising gap junction intercellular communication. Methods: Cell culture models of hyperglycemia involving endothelial cells, pericytes, and Muller cells were used in this study. Cells were exposed to high glucose (HG: 30 mM) for 7 days and harvested for analysis of Cx43, ZO-1, rab20, and β-actin by Western blot and subsequent densitometric analyses using imageJ software. Immunoprecipitation was performed to identify rab20 by Western blot analysis. Localization and distribution of the tight junction and gap junction proteins were determined by immunostaining. Cells immunostained for Cx43 and ZO-1 were digitally photographed under immunofluorescence microscopy and assessed for protein localization and distribution. To determine the effect of reduced rab20, cells were transfected with rab20 siRNA in the presence of Lipofectin; scrambled siRNA was used as control. To identify cells undergoing apoptosis, TUNEL assay was performed. Results: Western blot analysis revealed that HG significantly reduced Cx43 protein expression in rMC-1 (64% of N) and cocultures of rMC-1 and BRPs (72% of N). Similarly, Cx43 and ZO-1 immunostaining were significantly reduced in these cells grown in HG condition. Western blot analysis also revealed that HG significantly upregulated rab20 (129% of N) protein expression. Under HG condition, an increased number of TUNEL+ cells was detected using TUNEL assay (7.3 vs. 1.5 TUNEL+ cells per 1000 cells). HG cells transfected with rab20 siRNA significantly reduced the number of apoptotic cells (1.5 vs. 7.3 TUNEL+ cells per 1000 cells). Conclusion: Findings from this study indicate that HG-induced disturbed gap junction intercellular communication may contribute to retinal vascular cell and Muller cell apoptosis. HG-induced overexpression of rab20 may play a significant role in reducing Cx43 expression and compromising cell-cell communication associated with the pathogenesis of diabetic retinopathy.

Diabetic retinopathy (DR) is a retinal vascular disease associated with diabetes and it is one of the most common causes of blindness worldwide. Diabetic patients regularly attend retinal screening in which digital retinal images are captured. These images undergo thorough analysis by trained individuals, which can be a very time consuming and costly task due to the large diabetic population. Therefore, this is a field that would greatly benefit from the introduction of automated detection systems. This project aims to automatically detect proliferative diabetic retinopathy (PDR), which is the most advanced stage of the disease and poses a high risk of severe visual impairment. The hallmark of PDR is neovascularisation, the growth of abnormal new vessels. Their tortuous, convoluted and obscure appearance can make them difficult to detect. In this thesis, we present a methodology based on the novel approach of creating two different segmented vessel maps. Segmentation methods include a standard line operator approach and a novel modified line operator approach. The former targets the accurate segmentation of new vessels and the latter targets the reduction of false responses to non-vessel edges. Both generated binary vessel maps hold vital information which is processed separately using a dual classification framework. Features are measured from each binary vessel map to produce two separate feature sets. Independent classification is performed for each feature set using a support vector machine (SVM) classifier. The system then combines these individual classification outcomes to produce a final decision. The proposed methodology, using a dataset of 60 images, achieves a sensitivity of 100.00% and a specificity of 92.50% on a per image basis and a sensitivity of 87.93% and a specificity of 94.40% on a per patch basis. The thesis also presents an investigation into the search for the most suitable features for the classification of PDR. This entails the expansion of the feature vector, followed by feature selection using a genetic algorithm based approach. This provides an improvement in results, which now stand at a sensitivity and specificity 3 of 100.00% and 97.50% respectively on a per image basis and 91.38% and 96.00% respectively on a per patch basis. A final extension to the project sees the framework of dual classification further explored, by comparing the results of dual SVM classification with dual ensemble classification. The results of the dual ensemble approach are deemed inferior, achieving a sensitivity and specificity of 100.00% and 95.00% respectively on a per image basis and 81.03% and 95.20% respectively on a per patch basis.