• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 11
  • 5
  • 2
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • Tagged with
  • 23
  • 23
  • 23
  • 7
  • 7
  • 5
  • 5
  • 5
  • 5
  • 4
  • 4
  • 4
  • 4
  • 4
  • 3
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
21

Chemotherapy, estrogen, and cognition : neuroimaging and genetic variation

Conroy, Susan Kim 25 February 2014 (has links)
Indiana University-Purdue University Indianapolis (IUPUI) / The time course and biological mechanisms by which breast cancer (BC) and/or alterations in estrogen status lead to cognitive and brain changes remain unclear. The studies presented here use neuroimaging, cognitive testing, genetics, and biomarkers to investigate how post-chemotherapy interval (PCI), chemotherapy-induced amenorrhea (CIA), and genetic variation in the estrogen pathway affect the brain. Chapter 1 examines the association of post-chemotherapy interval (PCI) with gray matter density (GMD) and working memory-related brain activation in BC survivors (mean PCI 6.4, range 3-10 years). PCI was positively associated with GMD and activation in the right frontal lobe, and GMD in this region was correlated with global neuropsychological function. In regions where BC survivors showed decreased GMD compared to controls, this was inversely related to oxidative DNA damage and learning and memory scores. This is the first study to show neural effects of PCI and relate DNA damage to brain alterations in BC survivors. Chapter 2 demonstrates prospectively, in an independent cohort, decreased combined magnitudes of brain activation and deactivation from pre-to post-chemotherapy in patients undergoing CIA compared to both postmenopausal BC patients undergoing chemotherapy and healthy controls. CIA’s change in activity magnitude was strongly correlated with change in processing speed, suggesting this activity increase reflects effective cognitive compensation. These results demonstrate that the pattern of change in brain activity from pre- to post-chemotherapy varies according to pre-treatment menopausal status. Chapter 3 presents the effects of variation in ESR1, the gene that codes for estrogen receptor-α, on brain structure in healthy older adults. ESR1 variation was associated with hippocampus and amygdala volumes, particularly in females. Single nucleotide polymorphism (SNP) rs9340799 influenced cortical GMD and thickness differentially by gender. Apolipoprotein E (APOE)-ε4 carrier status modulated the effect of SNP rs2234693 on amygdala volumes in women. This study showed that genetic variation in estrogen relates to brain morphology in ways that differ by sex, brain region and APOE-ε4 carrier status. The three studies presented here explore the interplay of BC, estrogen, and cognition, showing that PCI, CIA, and ESR1 genotype influence brain phenotypes. Cognitive correlates of neuroimaging findings indicate potential clinical significance of these results.
22

Evaluation of the IrisPlex DNA-based eye color prediction tool in the United States

Dembinski, Gina M. 31 July 2014 (has links)
Indiana University-Purdue University Indianapolis (IUPUI) / DNA phenotyping is a rapidly developing area of research in forensic biology. Externally visible characteristics (EVCs) can be determined based on genotype data, specifically from single nucleotide polymorphisms (SNPs). These SNPs are chosen based on their association with genes related to the phenotypic expression of interest, with known examples in eye, hair, and skin color traits. DNA phenotyping has forensic importance when unknown biological samples at a crime scene do not result in a criminal database hit; a phenotype profile of the sample can therefore be used to develop investigational leads. IrisPlex, an eye color prediction assay, has previously shown high prediction rates for blue and brown eye color in a European population. The objective of this work was to evaluate its utility in a North American population. We evaluated the six SNPs included in the IrisPlex assay in an admixed population sample collected from a U.S.A. college campus. We used a quantitative method of eye color classification based on (RGB) color components of digital photographs of the eye taken from each study volunteer and placed in one of three eye color categories: brown, intermediate, and blue. Objective color classification was shown to correlate with basic human visual determination making it a feasible option for use in future prediction assay development. In the original IrisPlex study with the Dutch samples, they correct prediction rates achieved were 91.6% for blue eye color and 87.5% for brown eye color. No intermediate eyes were tested. Using these samples and various models, the maximum prediction accuracies of the IrisPlex system achieved was 93% and 33% correct brown and blue eye color predictions, respectively, and 11% for intermediate eye colors. The differences in prediction accuracies is attributed to the genetic differences in allele frequencies within the sample populations tested. Future developments should include incorporation of additional informative SNPs, specifically related to the intermediate eye color, and we recommend the use of a Bayesian approach as a prediction model as likelihood ratios can be determined for reporting purposes.
23

ROLE OF GENOMIC COPY NUMBER VARIATION IN ALZHEIMER'S DISEASE AND MILD COGNITIVE IMPAIRMENT

Swaminathan, Shanker 14 February 2013 (has links)
Indiana University-Purdue University Indianapolis (IUPUI) / Alzheimer's disease (AD) is the most common form of dementia defined by loss in memory and cognitive abilities severe enough to interfere significantly with daily life activities. Amnestic mild cognitive impairment (MCI) is a clinical condition in which an individual has memory deficits not normal for the individual's age, but not severe enough to interfere significantly with daily functioning. Every year, approximately 10-15% of individuals with MCI will progress to dementia. Currently, there is no treatment to slow or halt AD progression, but research studies are being conducted to identify causes that can lead to its earlier diagnosis and treatment. Genetic variation plays a key role in the development of AD, but not all genetic factors associated with the disease have been identified. Copy number variants (CNVs), a form of genetic variation, are DNA regions that have added genetic material (duplications) or loss of genetic material (deletions). The regions may overlap one or more genes possibly affecting their function. CNVs have been shown to play a role in certain diseases. At the start of this work, only one published study had examined CNVs in late-onset AD and none had examined MCI. In order to determine the possible involvement of CNVs in AD and MCI susceptibility, genome-wide CNV analyses were performed in participants from three cohorts: the ADNI cohort, the NIA-LOAD/NCRAD Family Study cohort, and a unique cohort of clinically characterized and neuropathologically verified individuals. Only participants with DNA samples extracted from blood/brain tissue were included in the analyses. CNV calls were generated using genome-wide array data available on these samples. After detailed quality review, case (AD and/or MCI)/control association analyses including candidate gene and genome-wide approaches were performed. Although no excess CNV burden was observed in cases compared to controls in the three cohorts, gene-based association analyses identified a number of genes including the AD candidate genes CHRFAM7A, RELN and DOPEY2. Thus, the present work highlights the possible role of CNVs in AD and MCI susceptibility warranting further investigation. Future work will include replication of the findings in independent samples and confirmation by molecular validation experiments.

Page generated in 0.119 seconds