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Brain-Reactive Antibodies: Molecular Specificity and Relationship to Biological AgingApte, Vaijayanti 05 1900 (has links)
Brain-reactive antibodies (BRA) increase in frequency with age in several mammalian species and may be involved in the pathogenesis of age-related dementia. In this experiment, the molecular specificity of BRA in mouse sera was determined using an immunoblot assay, and the relationship of BRA to longevity was studied by comparing the rate of formation of specific BRAs in diet restricted C57BL/6NNia, B6D2F1/NNia, and DBA/2NNia, genotypes which differ markedly in life-span.
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Biological aging quantification and its association with sleep in the Bogalusa heart studyJanuary 2021 (has links)
archives@tulane.edu / Background:
Human Biological Aging (BA) estimates are developed by human to better capture the gradual increase in the vulnerability of the aging body than chronological age. Human sleep dimensions have been suggested to be associated with human health indicators including cardiometabolic function, cognitive function and mortality. The objective of this study was to examine indicators of BA and their predictive validity using Klemera and Doubal’s Method (KDM), and Physiological Dysregulation Method (PDM) for quantifying BA, as well as to explore if phenotypical and genetic associations between sleep variables and BA estimates exist, using the Bogalusa Heart Study (BHS) – a community-based, cohort study.
Method:
In order to estimate BA, nineteen biomarkers were selected. Training datasets were from NHANES. The target dataset included 1,034 BHS subjects assessed between 2013-2016. Training was done separately for male and female, black and white participants. KDM and Mahalanobis Distance (DM) based PDM methods were used. Cognitive and physical performance testing were used to examine predictive validity.
The association between three sleep dimension variables and BA estimates were explored using 953 black and white BHS 2013-2016 subjects. Sleep duration in hours, chronotype scores and social jetlag in hours were the independent variables. BA estimates were the dependent variables.
Genotyping information from the BHS 2013-2016 were included (n=646) for genetic association. Related SNPs on morning chronotype were used to compute a genetic risk score (GRS) for BHS participants. Association between chronotype GRS and chronotype phenotype were explored.
Multivariate linear regression was used for all association analyses.
Results:
BA estimates were calculated using both the KDM and PDM methods. Linear regression showed that PDM BA estimates were associated with lower cognitive function physical performance tests. The effect sizes of all associations between PDM BA estimates and performance tests were of greater magnitude than between KDM estimates and performance tests. Short sleep duration and evening chronotype was associated with larger PDM BA estimates. Morning chronotype GRS was not associated with morning chronotype phenotype among BHS participants.
Conclusion:
PDM BA estimates are robust measures of biological aging in black and white men and women enrolled in the BHS. Insufficient sleep duration and evening chronotype may advance biological aging, regardless of gender, race and CA. We did not find association between morning chronotype GRS and morning chronotype phenotype. PDM BA estimates should be recommended for future aging studies using data from BHS participants. / 1 / Xunming Sun
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Systemic inflammation, mild cognitive impairment and Alzheimer’s disease: findings from the PREVENT studyDeCarlo, Correne A. 14 July 2016 (has links)
The search for reliable early indicators of age-related cognitive decline represents an important avenue in aging research. Most research on late-life development charts cognitive change as a function of chronological age (CA), however, although CA is a commonly used developmental index, it offers little insight into the mechanisms underlying cognitive decline. In contrast, biological age (BioAge), reflecting the vitality of essential biological processes, represents a promising operationalization of developmental time. My overall programmatic doctoral research interests involve the identification of biological risk factors that predict age-related cognitive decline, impairment and dementia. In this dissertation document, I present: an overview of my empirical contributions to the BioAge and cognitive aging literature throughout my doctoral training; the dissertation project which uses preliminary data from the PREVENT study and provides evidence that elevated plasma pro-inflammatory proteins are associated with cognitive status (healthy controls (HC) vs Alzheimer’s disease dementia (AD)), cognitive performance and are related to poorer cognitive performance in amnestic mild cognitive impairment (a-MCI); and a discussion on the broad implications of the project results and future directions in BioAge research. / Graduate
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Collective Processes In Cellular ReprogrammingMohammadzadehhashtroud, Aida 16 May 2024 (has links)
Epigenetics comprises chemical modifications of the DNA and the proteins that the DNA is wrapped around them. These modifications play key roles in establishing and maintaining cellular identity throughout development and adulthood. In recent years, it has become increasingly clear that these actions are more dynamic than initially believed. The alteration of cellular identities during regeneration, ageing, and the formation of tumors is closely linked to systematic changes in epigenetic modifiers. The emergence of cutting-edge single-cell sequencing technologies has enabled thorough explorations of biological processes with high molecular precision. Nevertheless, the regulation of cellular behavior is intricately tied to collective processes occurring in both spatial and temporal dimensions, operating on the mesoscopic and macroscopic scales. However, these larger scales cannot be straightforwardly deduced from microscopic measurements along the DNA sequence. Consequently, the findings obtained from sequencing experiments stay at the descriptive level until they are coupled with methodologies capable of discerning collective degrees of freedom. Here, using statistical physics tools and sequencing technologies, we study the collective processes underlying epigenetic dynamics in cells that change their identity over time. Specifically, we investigate collective epigenetic processes during ageing and the reprogramming of cells after injury.
In the first part of this thesis, we study the mechanistic basis of epigenetic modifications during ageing. Despite the accuracy of machine learning models in predicting the biological age based on epigenetic DNA methylation marks, these tools do not inform about the mechanistic basis of epigenetic ageing. We show that epigenetic ageing is reflected in systematic and collective changes in DNA methylation marks during ageing, which manifests in the stereotypical behavior of two-point correlation functions. We devise a stochastic theory that comprises competition of antagonistic enzymes at the boundaries of genomic regions with atypically high content of cytosine-guanine pairs. We systematically coarse-grain this theory to derive a macroscopic description in terms of a phase-field theory. This model predicts the changes in two-point correlation functions during ageing and explains diverse observations in the field of epigenetic ageing.
In the second part of this thesis, we study the collective epigenetic processes during the regeneration of the liver after injury. In particular, we study the interplay between DNA methylation and the accessibility of chromatin and show the necessity for emergent memory of past injuries in the system. This memory is achieved by considering an effective projection between different scales of epigenetic modifications.
In total, in this thesis, we derived theoretical descriptions of epigenetic processes that have so far only been studied descriptively. We showed that both epigenetic alterations during ageing and during reprogramming rely on an interplay between collective biochemical processes and the geometry of the DNA. With this work, we show how linear DNA sequencing can inform about collective epigenetic processes in space and time.
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