Browsing Theses and Dissertations, Electronic (ETDs) by Author "Abadir, Peter"
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ItemCreating a Character Animation-based Interactive Frailty Model to Support Better Primary Care Implementation and Planning for Older Adults(Johns Hopkins University, 2019-03-25) Kethu, Lohitha; Fairman, Jennifer E; Abadir, Peter; Buta, BrianAs global populations age, it is imperative for clinicians and researchers to understand and apply measures of frailty syndrome to support healthy aging. Frailty syndrome is defined as a clinically recognizable state of increased vulnerability resulting from aging-associated declines in reserve and function across multiple physiologic systems, compromising the ability to cope with every day or acute stressors. Frailty predicts surgery outcomes, waitlist times, cancer therapy tolerance, disability, institutionalization, morbidity, and mortality. Insufficient understanding of the complex nature of frailty from molecular changes, to physiology to clinical changes, is a major challenge for clinicians and researchers that focus on uni-dimensional (one factor at a time) molecular pathways to late-life decline connections. In a collaboration between clinicians, frailty researchers, and medical illustrators, a multidimensional, character animation-based resource was built, which articulates the aging and frailty-related changes from the cellular level to the clinical level, and provides visualizations that facilitate an understanding of a multidimensional, holistic frailty theory. With guidance from the Frailty and Multisystem Dysregulation Working Group at the Center on Aging and Health, a two-part 3D character-animated, web-based, interactive 2D and 3D module was created to convey both “2D” clinical theory and “3D” real patient experience, created in ZBrush and Cinema 4D. The interactive portion of the module was created through Blender and Verge3D. ItemEmergent patterns of cellular phenotypes in health and disease(Johns Hopkins University, 2015-10-22) Phillip, Jude Marvin; Walton, Jeremy; Wirtz, Denis; Abadir, Peter; Shih, Ie-Ming; Konstantopoulos, Konstantinos; Gerecht, Sharon; Cui, HonggangThe cellular framework that constitutes the building blocks of every living organism undergoes significant changes and transformations throughout its live time. In humans, many processes that involve these cellular changes can greatly influence the healthspan and survival of individuals, two of such processes include: aging and cancer. The two related, yet independent processes both arise due to the deterioration of ‘naïve’ cellular function, and the deficiency—later inability, of cells to properly regulate its physiology. Published studies have demonstrated a bi-phasic relationship between cancer and aging. With the incidences of cancer increasing with increasing age, followed by a plateau point and subsequent decrease; with cancer-type dependent shifts in this plateau point with age. There are a multitude of factors that affect the initiation and rate of progression of these cellular changes, and they stem from both intrinsic factors—such as the individuals’ underlying molecular and phenotypic profiles (i.e. genetics and protein expressions)—and extrinsic factors, such as lifestyle and environmental influences. To gain better understanding of these two naturally occurring processes, I took a piece-wise approach and asked two overarching questions. In regards to aging I asked how does the biochemical and biophysical features of cells construct the phenotypic portrait of human aging, and cane it be used to determine the biological age of individuals? Likewise, in regards to cancer: how does the cells’ physical properties associate with cancer progression and metastasis, and can it predict metastatic state based on the features of individual cells? In the first part of this study, I focus on human aging. Many studies have shown that there are marked changes in the cells’ molecular profiles and phenotypic behaviors with increasing age. To better understand this I procured a cohort of primary dermal fibroblasts and measured various aspects of the cellular biochemical framework (cell secretions, DNA damage response and DNA organization, cytoskeletal content and organization, and ATP content), as well as cellular biophysical features (morphology, motility, wound closure, traction strength, and cytoplasmic rheological properties). With this comprehensive approach, I was able to quantify age-dependent changes in various cellular features, and use these features to further predict biological age with a high degree of certainty. Knowing the biological age of an individual is important, since it is now apparent from the literature that the biological age is a better predictor of human healthspan and longevity than their corresponding chronological age. Secondly, according to the American Cancer Society, two out of every five persons in the US will develop cancer during his/her lifetime, with ninety percent of cancer-related deaths resulting from metastases, i.e. the migration of cancer cells from the primary tumor to distal sites in other organs. Since the completion of the Human Genome Project, researchers have focused on trying to understand the genetic basis of metastasis in an effort to better predict disease progression and uncover new therapeutic targets. However, possibly due to the inherent heterogeneity of cancer, no genetic signatures that clearly delineate cells from the primary tumors versus cells from metastatic sites have been found. Recent estimates suggest that millions of cells are shed from a primary tumor site each day, yet, progression to metastatic disease often take years, suggesting that metastasis is a highly inefficient process. From a biophysical perspective, I reasoned that in order to successfully overcome the difficult multi-step metastatic cascade—invasion and migration through the dense, tortuous stromal matrix, intravasation, survival of shear forces of blood flow, successful re-attachment to blood vessel walls, colonization at distal sites, and reactivation following dormancy—metastatic cells may share precise sets of physical properties. And these key physical properties (which can be thought of as the ensemble effects of it’s genetic, epigenetic and proteomic profiles, etc.) may contribute to the progression and diminished response to therapeutics exhibited by metastatic cells. Using a cohort of 13 clinically annotated PDAC (Pancreatic ductal adenocarcinoma) patient samples, cells were subjected to a phenotyping platform that I have co-developed—htCP (high-throughput cell phenotyping). This study revealed that using biophysical features described by the variations in the cellular morphological features, I was able to discover a phenotypic signature for metastasis, demonstrated in pancreatic and breast cancers, for both 2D and 3D environments. ItemLinks of Genetic Risk for Short Sleep Duration with Cognitive, Functional, and Biological Aging Outcomes in Older Adults(Johns Hopkins University, 2021-07-15) Smail, Emily J; Abadir, Peter; Maher, Brion; Spira, Adam; Schrack, JenniferBackground: Older adults are disproportionately susceptible to sleep problems. Nearly one-half of older adults live with insomnia and almost 7% experience excessive daytime sleepiness on a daily or almost daily basis. Sleep has been implicated in a number of health conditions (e.g., obesity, dementia) and is associated with several social and economic outcomes including workplace injuries and motor vehicle accidents. The U.S. population of older adults is expected to double from around 50 million to nearly 100 million individuals in the next 40 years, suggesting an increased prevalence of sleep disturbance and aging-related outcomes such as chronic disease, disability, and Alzheimer’s disease. Understanding the mechanisms and consequences of sleep disturbance can inform prevention and treatment strategies for sleep disturbances in older adults. One way to uncover mechanisms is using genetic markers of risk. However, little work has examined genetic risk for short sleep duration with measures of cognitive and physical performance or biological markers of aging. Method: Data for these analyses came from the Baltimore Longitudinal Study of Aging (BLSA), an ongoing, prospective cohort study of over 3,200 participants. Polygenic risk scores were calculated using genetic data ascertained between 1986 and 2017 on a subset of 848 participants. Cognitive and physical performance outcomes were gathered using data from each BLSA study visit, whereas biological markers of aging were calculated using the Horvath DNA methylation age calculator from epigenetic data, collected on 820 participants between 2008 and 2012. We investigated prospective links of polygenic risk for short sleep duration with cognitive performance (n=1,242) and physical performance (n=1,373-1,458) using linear mixed effects models, and cross-sectional associations with biological aging markers (n=467) using linear regression models. We also investigated associations of self-reported sleep duration with the biological aging markers (n=615). Across models, participants were predominantly white and male. All models were adjusted for age, sex, years of education, and medical comorbidities. Results: Our findings show no significant associations between polygenic risk score for short sleep duration and cognitive domain scores, but significant associations between polygenic risk score for short sleep duration and decline in SPPB score and some biological measures of aging (i.e., estimated granulocyte count and plasminogen activator inhibitor-1), though these results are attenuated in fully adjusted models. In models investigating phenotypic sleep duration as the primary predictor and biological measures of aging as the outcome, relative to individuals sleeping ≤6 hours, those sleeping >7 hours, showed faster Hannum age-acceleration, and greater PhenoAge, GrimAge, estimated granulocyte count, and PAI-1. We also found moderation of associations of self-reported sleep duration with some biological measures by age and sex. Implications: Higher genetic risk for short sleep duration is associated, to varying degrees, with faster decline in physical performance and worse levels of biological markers of accelerated aging among older adults. Findings suggest that shorter sleep duration may contribute to poor physical performance and accelerated aging. Prospective studies in larger samples are needed to examine whether these effects are robust to the inclusion of confounders, and whether effect estimates change across demographic subgroups.