As cardiovascular disease remains the global leading cause of death, there is an urgent need to study the pathophysiology of the heart and to effectively evaluate cardioprotective drugs. Due to the difficulty in studying the human heart in vivo and sourcing human heart tissues, induced pluripotent stem cells (iPSCs) have provided a promising alternative for modeling cardiac diseases and evaluating candidate drugs. In recent years, computational methods, including machine learning, have given rise to a new class of tools to evaluate cardiac function more rapidly and comprehensively. In this dissertation, I develop and apply computational tools to probe the function of human iPSC-derived cardiac models (Aim 1), apply machine learning methods in the context of cardiomyocyte disease phenotyping and cardioactive drug profiling (Aim 2), and develop a pipeline for deep learning-driven cardiac fibroblast phenotypic drug discovery (Aim 3).

No / Cardiovascular disease is the principal cause of death in patients with type 2 diabetes (T2DM). Exposure of the vasculature to metabolic disturbances leaves a persistent imprint on vascular walls, and specifically on smooth muscle cells (SMC) that favours their dysfunction and potentially underlies macrovascular complications of T2DM. Current diabetes therapies and continued development of newer treatments has led to the ability to achieve more efficient glycaemic control. There is also some evidence to suggest that some of these treatments may exert favourable pleiotropic effects, some of which may be at the level of SMC. However, emerging interest in epigenetic markers as determinants of vascular disease, and a putative link with diabetes, opens the possibility for new avenues to develop robust and specific new therapies. These will likely need to target cell-specific epigenetic changes such as effectors of DNA histone modifications that promote or inhibit gene transcription, and/or microRNAs capable of regulating entire cellular pathways through target gene repression. The growing epidemic of T2DM worldwide, and its attendant cardiovascular mortality, dictates a need for novel therapies and personalised approaches to ameliorate vascular complications in this vulnerable population.

Yes / Background/purpose Coronary heart disease is the leading cause of morbidity in patients with type 2 diabetes mellitus (T2DM), frequently resulting in a requirement for coronary revascularization using the internal mammary artery (IMA) or saphenous vein (SV). Patency rates of SV grafts are inferior to IMA and further impaired by T2DM whilst IMA patencies appear similar in both populations. Smooth muscle cells (SMC) play a pivotal role in graft integration; we therefore examined the phenotype and proliferative function of IMA- and SV-SMC isolated from non-diabetic (ND) patients or those diagnosed with T2DM. Methods/materials SMC were cultured from fragments of SV or IMA. Morphology was analyzed under light microscopy (spread cell area measurements) and confocal microscopy (F-actin staining). Proliferation was analyzed by cell counting. Levels of RhoA mRNA, protein and activity were measured by real-time RT-PCR, western blotting and G-LISA respectively. Results IMA-SMC from T2DM and ND patients were indistinguishable in both morphology and function. By comparison, SV-SMC from T2DM patients exhibited significantly larger spread cell areas (1.5-fold increase, P < 0.05), truncated F-actin fibers and reduced proliferation (33% reduction, P < 0.05). Furthermore, lower expression and activity of RhoA were observed in SV-SMC of T2DM patients (37% reduction in expression, P < 0.05 and 43% reduction in activity, P < 0.01). Conclusions IMA-SMC appear impervious to phenotypic modulation by T2DM. In contrast, SV-SMC from T2DM patients exhibit phenotypic and functional changes accompanied by reduced RhoA activity. These aberrancies may be epigenetic in nature, compromising SMC plasticity and SV graft adaptation in T2DM patients.

Yes / Cardiovascular disease is a leading cause of morbidity and mortality. Smooth muscle cells (SMC) comprising the vascular wall can switch phenotypes from contractile to synthetic, which can promote the development of aberrant remodelling and intimal hyperplasia (IH). MicroRNA‐21 (miR‐21) is a short, non‐coding RNA that has been implicated in cardiovascular diseases including proliferative vascular disease and ischaemic heart disease. However, its involvement in the complex development of atherosclerosis has yet to be ascertained. Smooth muscle cells (SMC) were isolated from human saphenous veins (SV). miR‐21 was over‐expressed and the impact of this on morphology, proliferation, gene and protein expression related to synthetic SMC phenotypes monitored. Over‐expression of miR‐21 increased the spread cell area and proliferative capacity of SV‐SMC and expression of MMP‐1, whilst reducing RECK protein, indicating a switch to the synthetic phenotype. Furthermore, platelet‐derived growth factor BB (PDGF‐BB; a growth factor implicated in vasculoproliferative conditions) was able to induce miR‐21 expression via the PI3K and ERK signalling pathways. This study has revealed a mechanism whereby PDGF‐BB induces expression of miR‐21 in SV‐SMC, subsequently driving conversion to a synthetic SMC phenotype, propagating the development of IH. Thus, these signaling pathways may be attractive therapeutic targets to minimise progression of the disease. / King Saud University; College of Medicine , Riyadh, Saudi Arabia

Understanding the genetic basis of complex disease is a critical research goal due to the immense, worldwide burden of these diseases. Observational data, such as electronic health records (EHR), offer numerous advantages in the study of complex disease genetics. These include their large scale, cost-effectiveness, information on many different conditions, and future scalability with the widespread adoption of EHRs. Observational data, however, are challenging for research due to noise and confounding. EHR data reflect factors including the healthcare process and access to care, as well as broader societal effects like systemic biases. Billing codes for complex diseases may be recorded when no diagnosis is intended, and they may be missing when a diagnosis would be correct. Overall, systematic errors distort the genetic signal available for study and motivate taking a closer look at the ways that phenotypes can be defined using observational data. In Chapter 3, we introduce MaxGCP, a novel phenotyping method designed to purify the genetic signal in observational data. Our approach optimizes a phenotype definition to maximize its coheritability with the complex trait of interest. We first validated this method in simulations of 5000 different phenotypes across a wide range of simulation parameters, demonstrating that the method improves genome-wide association study (GWAS) power compared to conventional methods. Having evaluated it in simulation, we next applied the method in real data analyses of stroke and Alzheimer’s disease. By comparing GWAS associations to high-quality, independent test data, we were able to compare both the sensitivity and specificity of our method. This analysis similarly found that MaxGCP boosts GWAS power compared to previous methods. In Chapter 4, we extend this work to increase the speed and re-usability of pan-biobank GWAS with another new method, Indirect GWAS. Large scale, pan-biobank studies provide a powerful resource in complex disease genetics, generating shareable summary statistics on thousands of phenotypes. Biobank-scale GWAS have two notable limitations: they are resource-intensive to compute and do not inform about hand-crafted phenotype definitions, which are often more relevant to study. Our method uses summary statistics to addresses these limitations. It computes GWAS summary statistics for any phenotype defined as a linear combination of other phenotypes. We demonstrate a number of useful applications, including an order of magnitude improvement in runtime for large-pan-biobank GWAS and ultra-rapid (less than one minute) GWAS on hand-crafted phenotype definitions using only summary statistics. Through the development of new computational and statistical methods, this work demonstrates the importance and power of the phenotype side of genetic association studies, and it provides two new approaches that can improve future genetic studies of complex disease.

Phenotypic profiling systematically maps and analyzes observable traits (phenotypes) exhibited in cells, tissues, organisms or systems in response to various conditions, including chemical, genetic and disease perturbations. This approach seeks to comprehensively understand the functional consequences of perturbations on biological systems, thereby informing diverse research areas such as drug discovery, disease modeling, functional genomics and systems biology. Corresponding techniques should capture high-dimensional features to distinguish phenotypes affected by different conditions. Current methods mainly include fluorescence imaging, mass spectrometry and omics technologies, coupled with computational analysis, to quantify diverse features such as morphology, metabolism and gene expression in response to perturbations. Yet, they face challenges of high costs, complicated operations and strong batch effects. Vibrational imaging offers an alternative for phenotypic profiling, providing a sensitive, cost-effective and easily operated approach to capture the biochemical fingerprint of phenotypes. Among vibrational imaging techniques, infrared (IR) imaging has further advantages of high throughput, fast imaging speed and full spectrum coverage compared with Raman imaging. However, current biomedical applications of IR imaging mainly concentrate on "digital disease pathology", which uses label-free IR imaging with machine learning for tissue pathology classification and disease diagnosis. The thesis contributes as the first comprehensive study of using IR imaging for phenotypic profiling, focusing on three key areas. First, IR-active vibrational probes are systematically designed to enhance metabolic specificity, thereby enriching measured features and improving sensitivity and specificity for phenotype discrimination. Second, experimental workflows are established for phenotypic profiling using IR imaging across biological samples at various levels, including cellular, tissue and organ, in response to drug and disease perturbations. Lastly, complete data analysis pipelines are developed, including data preprocessing, statistical analysis and machine learning methods, with additional algorithmic developments for analyzing and mapping phenotypes. Chapter 1 lays the groundwork for IR imaging by delving into the theory of IR spectroscopy theory and the instrumentation of IR imaging, establishing a foundation for subsequent studies. Chapter 2 discusses the principles of popular machine learning methods applied in IR imaging, including supervised learning, unsupervised learning and deep learning, providing the algorithmic backbone for later chapters. Additionally, it provides an overview of existing biomedical applications using label-free IR imaging combined with machine learning, facilitating a deeper understanding of the current research landscape and the focal points of IR imaging for traditional biomedical studies. Chapter 3-5 focus on applying IR imaging coupled with machine learning for novel application of phenotypic profiling. Chapter 3 explores the design and development of IR-active vibrational probes for IR imaging. Three types of vibrational probes, including azide, 13C-based probes and deuterium-based probes are introduced to study dynamic metabolic activities of protein, lipids and carbohydrates in cells, small organisms and mice for the first time. The developed probes largely improve the metabolic specificity of IR imaging, enhancing the sensitivity of IR imaging towards different phenotypes. Chapter 4 studies the combination of IR imaging, heavy water labeling and unsupervised learning for tissue metabolic profiling, which provides a novel method to map metabolic tissue atlas in complex mammalian systems. In particular, cell type-, tissue- and organ-specific metabolic profiles are identified with spatial information in situ. In addition, this method further captures metabolic changes during brain development and characterized intratumor metabolic heterogeneity of glioblastoma, showing great promise for disease modeling. Chapter 5 developed Vibrational Painting (VIBRANT), a method using IR imaging, multiplexed vibrational probes and supervised learning for cellular phenotypic profiling of drug perturbations. Three IR-active vibrational probes were designed to measure distinct essential metabolic activities in human cancer cells. More than 20,000 single-cell drug responses were collected, corresponding to 23 drug treatments. Supervised learning is used to accurately predict drug mechanism of action at single-cell level with minimal batch effects. We further designed an algorithm to discover drug candidates with novel mechanisms of action and evaluate drug combinations. Overall, VIBRANT has demonstrated great potential across multiple areas of phenotypic drug screening.

Doctor of Philosophy / Department of Plant Pathology / William W. Bockus / James P. Stack / Wheat blast, caused by the Triticum pathotype of Magnaporthe oryzae (MoT), is a serious disease of wheat causing yield failures and significant economic losses during epidemic years in Brazil, Paraguay, and Bolivia. Although outbreaks occur only sporadically, wheat blast is considered a major disease affecting wheat production in South America and may be a threat to the wheat crop in the United States. Wheat is a major crop in the U.S. and wheat exports from the U.S. are important to food security of several countries around the World. Thus, it is important to understand the potential for MoT entry and establishment into the U.S. and to test U.S. wheat cultivars for susceptibility to MoT. The hypotheses of this research project were a) importing wheat grain from Brazil does not pose a risk for MoT establishment in the U.S., and b) resistance to MoT head infection does not exist in U.S. hard red winter wheat elite cultivars. Quantitative pathway analysis models were used to estimate the risk of MoT entry and establishment, in the coterminous U.S. and in a more targeted area within southeast North Carolina, via the importation of wheat grain from Brazil. The pathway model predicted that significant risk for MoT entry and establishment exists in some areas of the U.S. However, in approximately 60% of the coterminous U.S. winter wheat production areas the risk of MoT establishment was estimated to be zero. With respect to winter wheat growing areas in the U.S., conditions for MoT establishment and wheat blast outbreak occur only in small, restricted geographic areas. A higher resolution pathway analysis based on a ground transportation corridor in North Carolina indicated that conditions for MoT establishment exist seven out of ten years. Among U.S. cultivars tested, a continuum in severity to head blast was observed; cultivars Everest and Karl 92 were highly susceptible with more than 90% disease severity, while cultivars PostRock, Jackpot, Overley, Jagalene, Jagger, and Santa Fe showed less than 3% infection.

Nepakankama mityba iki nėštumo ir per nėštumą gali lemti palikuonio svorio pokyčius, vėlesnę brandą ar lėtines neinfekcines ligas suaugus. Darbo tikslas: Įvertinti mitybos iki nėštumo ir per nėštumą įtaką žiurkių palikuonių fizinei būklei. Uždaviniai: 1. Nustatyti ir palyginti žiurkių palikuonių svorio kitimo tendencijas tarp pirmos ir antros palikuonių kartų. 2. Įvertinti morfologinius pirmos ir antros kartos palikuonių išvaizdos ir elgsenos pokyčius. Tyrime naudotos 12 motininių žiurkių patelių ir 121 palikuonis. Žiurkių maitinimas vyko nustatytomis eksperimento sąlygomis: I eksperimentinės grupės (N=5) žiurkės buvo 50 proc. ribotos maisto 1 mėnesį iki nėštumo ir per visą nėštumo laikotarpį, II eksperimentinės grupės (N=5) žiurkės buvo ribotos 50 proc. maisto 1 mėnesį iki nėštumo, III eksperimentinė grupė (N=2) – kontrolinė, buvo maitinama ad libitum (apie 20 g/p). Vėliau visų grupių žiurkės šertos ad libitum. Palikuonys sverti kartą per savaitę, vertinta metabolinį stresą patyrusių ir nepatyrusių žiurkių palikuonių išvaizda, elgsena ir kiti metabolinio streso požymiai: domėjimasis aplinka, bailumas, agresyvumas, nervingumas. Rezultatai: 1. &#9642; Suaugę pirmos kartos iki nėštumo ir per nėštumą maisto medžiagų ribojimą patyrusių žiurkių vyriškos lyties palikuonys sveria reikšmingai daugiau už kitas grupes; &#9642; Suaugę antros kartos tik iki nėštumo maisto medžiagų ribojimą patyrusių žiurkių vyriškos lyties palikuonys sveria reikšmingai daugiau nei kitų grupių palikuonys... [toliau žr. visą tekstą] / Unsufficient diet before pregnancy or in time of pregnancy can lead to inadequate weight of offspring, delayed maturation as well as obesity and greater risk of noncommunicable diseases in adulthood. The main objective of this study was to explore if there is a change in rat offspring’s body weight that can be attributed to maternal nutrition. Materials and methods. The animals were housed under standard conditions in the vivarium of the Institute of Biochemistry. All animal procedures are in accordance with the The State Food and Veterinary Service. The cohort of 12 mature female Wistar rats was divided into 3 groups with respect to nutritional restriction. The rats were fed either a control (1 group) or restricted diet (2 groups): one experimental group was food-restricted prior to pregnancy and the other - one month prior and through the pregnancy period. Both food-restricted rat groups received 50 percent less of the feed eaten in the control group. After 1 month maternal rats were mated. After weaning all pups were fed with control diet ad libitum. Pups were weighted weekly with the same, calibrated scales. After 4 months female offspring were mated following a standard above mentioned procedure. 2nd offspring generation was kept and weighted under the same standardized conditions. We also observed and evaluated offspring appearance, behavior and other signs of metabolic stress: interest in the environment, fear, aggressiveness, nervousness. Results show that 1... [to full text]

Le syndrome du QT long congénital (LQTS) est une canalopathie génétique, à l’origine de syncopes et mort subite. Le dépistage génétique identifie des variantes génétiques dans 50-70% des cas, suggérant l’implication d’autres gènes. Nous avons recueilli les caractéristiques des patients avec un LQTS à l’ICM, et recruté 12 patients avec un génotype négatif pour le LQTS pour un séquençage à haut débit des exons afin d’identifier de nouvelles variantes causales. Nous avons développé une approche analytique par étapes : (1) les gènes connus du, (2) les gènes dans des loci identifiés par des études d’association sur le QT, et (3) les gènes montrant la même variante chez plusieurs patients. L’analyse génétique a identifié de nouvelles variantes dans: (1) KCNJ2, ANK2 et AKAP9, et (2) dans NOS1AP. (3) Deux patientes avec des phénotypes semblables présentent la même variante homozygote dans TECRL, un nouveau gène candidat dont le rôle est inconnu. / Long QT syndrome (LQTS) is a channelopathy, causing syncope and sudden death. Genetic testing of individuals identifies genetic variants in up to 50-70% of cases, suggesting that additional genes may be involved. We have identified 50 patients with a diagnosis of LQTS at MHI, and recruited 12 patients reported negative for clinical testing of mutations in LQTS for a whole-exome next generation DNA sequencing approach in order to identify new variants and candidate genes. We have developed a stepwise analytic approach that focuses on (1) the known LQTS genes, (2) the genes in loci identified in genome-wide association studies of QT-interval, and (3) the loci showing variants across multiple patients. Our approach identified new variants in (1) KCNJ2, ANK2 and AKAP9, and (2) in NOS1AP. We identify 2 patients with a very similar phenotype with a homozygous variant in TECRL, an novel candidate gene with an unknown role in LQTS.

Grâce aux progrès expérimentaux permettant d'étudier deux phénotypes qui sont d'un intérêt majeur dans la compréhension des capacités d'adaptation d'A. gambiae s.s. à son environnement. Les différences de résistance à la dessiccation mises en évidence entre les différents caryotypes liés à l'inversion chromosomique 2La et entre les formes moléculaires M et S offrent des pistes intéressantes pour l'identification de facteurs génétiques impliqués dans la divergence écologique au sein de ce complexe d'espèces. / Thanks to progress in sequencing, the genomes of many organisms are known and available. Thus, functional genomics, the elucidation of gene function in sequenced genome, is currently booming. However, there is a gap between our growing knowledge in genetic and the current sparse information on phentoypic data ( "phenotype gap"). All organisms whose genome has been sequenced are facing this problem, including Anopheles gambiae.Anopheles gambiae sensu lato is a complex of sibling species, indistinguishable from a morphological point of view, present on almost the entire African continent. A. gambiae demonstrates an extreme environmental ubiquity and the characterization of phenotypes associated with adaptation to varying environments as well as the identification of genes involved in this adaptation is one of the main research axes in the post-genome area of this major malaria vector.We have studied some phenotypes associated with aridity and temperature in the nominal species of the A. gambiae complex. These two parameters are discriminent in the distribution of molecular forms and chromosomal inversions that characterize this species and may be involved in ecological divergence and speciation. We first measured desiccation resistance of adult mosquitoes of A. gambiae s.s. and we then studied the preferred temperatures of larvae in a choice device set-up (the shuttlebox). We compared the thermoregulation behavior and thermal preferences of a laboratory strain with field larvae of A. gambiae s.s. We also presented preliminary data on the preferred temperatures measured in field larvae of the S and M molecular forms.From a technical point of view, we improved an existing device for testing the survival of mosquitoes in highly desiccated conditions by coupling it with a video surveillance system, which help to increase the accuracy in determining the survival time, to avoid disturbing the system during the experiment and allow to test relatively large numbers of individuals. This study revealed a significant association between the 2La chromosomal inversion and resistance to desiccation in A. gambiae and highlighted the role of body size in the survival of this mosquito in dry environments.We also adapted a new device to study experimentally the thermopreference of A. gambiae s.s. larvae. The results showed that laboratory larvae and field M molecular form larvae had similar thermal preferences, consistent with the values of temperature usually found in natural breeding sites. In addition, the S molecular form larvae from southern Cameroon had preferences similar to those of northern Cameroon, regardless of karyotypes related to chromosomal inversions. In addition, the comparison of data for the M and S molecular forms larvae revealed that there was no significant difference in thermal preferences or in thermoregulatory behavior.Our results have contributed to the development of two experimental devices to study two phenotypes that are of major interest in understanding the adaptation of A. gambiae s.s. to its environment. The differences in desiccation resistance between the different karyotypes associated with the 2La chromosomal inversion and between the M and S molecular forms offer interesting new possibilities for the identification of genetic factors involved in their ecological divergence.