@phdthesis{EttlingergebHaberstumpf2023,
  author    = {Ettlinger [geb. Haberstumpf], Sophia},
  title     = {Pathological cognitive decline in the elderly participants of the Vogel Study},
  doi       = {10.25972/OPUS-26558},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-265582},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2023},
  abstract  = {Due to the global aging society and the enormous global incidence and prevalence rates that will result in the coming years, Alzheimer's Dementia (AD) represents a growing challenge for the health care system. The pathogenesis, which is unclear in parts, the chronic progression of AD, which often lasts for years, as well as insufficient diagnostic and therapeutic options complicate an adequate psychotherapeutic and medical approach to the disease. To date, AD is also considered an incurable disease. Therefore, it is essential to gain deeper insights into the early detection or even prevention of AD. Consideration of prodromal syndromes such as Mild Cognitive Impairment (MCI) can provide significant evidence about high-risk groups for AD progression and differentiate cognitively "normal" aging individuals from those with pathological cognitive decline. Thus, for example, functional Near-Infrared Spectroscopy (fNIRS) imaging helps identify early neurodegenerative processes. In contrast, potential risk factors and predictors of later-onset clinical symptoms of MCI and AD can most often be revealed and quantified via the use of neuropsychiatric test batteries. The present thesis consists of four studies and aimed to assess and describe the pathological cognitive decline in a sample of elderly study participants (age: ≥ 70 years; N = 604 at baseline) of the longitudinal, observational, and prospective "Vogel Study" from W{\"u}rzburg, Germany, who were primarily healthy at baseline, over two measurement time points approximately 3 years apart, to differentiate between healthy and diseased study participants and to define predictors of MCI/AD and longitudinal study dropout. Studies 1 and 2 differentiated healthy study participants from MCI patients based on the baseline hemodynamic response of the parietal cortex recorded by fNIRS during the processing of a paradigm (here: Angle Discrimination Task [ADT]) for visual-spatial processing performance. Neuronal hypoactivity was found in the MCI patients, with both healthy study participants and MCI patients showing higher superior and right hemispheric activation. MCI patients had more difficulty resolving the paradigm. Thus, no evidence of possible compensatory mechanisms was uncovered in the MCI patients. Study 3 first defined the four latent factors declarative memory, working memory, attention, and visual-spatial processing based on structural equation model (SEM) calculations of the sample using adequate measurement (in-)variant confirmatory factor models from the baseline assessment to the first of a total of two follow-up assessments after approximately 3 years. This allowed a dimensional assessment of pathological cognitive decline versus classificatory-categorical assignment (healthy/diseased) of the sample. In addition, the superiority of the latent factor approach over a composite approach was demonstrated. Next, using a mixed-model approach, predictive analyses were calculated for the prediction of latent factors at first follow-up by baseline risk factors. The sex of study participants proved to be the best predictor of cognitive change in all the cognitive domains, with females performing better than men in the memory domains. Specifically, for declarative memory, older age predicted lower performance regardless of sex. Additional predictive evidence emerged for low serum levels of Brain-Derived Neurotrophic Factor (BDNF) on lower attention performance and higher depression symptoms on lower visual-spatial processing performance. Study 4 further reported baseline predictors of study dropout at first follow-up. Cognitive performance, as defined in Study 3 using the four latent cognitive factors, was a predictor of study dropout for cognitive decline in the domains of declarative memory, attention, and visual-spatial processing. Conspicuous dementia screening on the Mini-Mental Status Examination (MMSE) also predicted dropout. Overall, both the use of fNIRS imaging to detect visual-spatial processing performance in the parietal cortex during applying ADT and the dimensional perspective of the neuropsychiatric test battery in the context of prediction and dropout analyses were found to be suitable for early detection research of MCI and AD. Finally, the results will be interpreted in the overall context and implications, limitations, and perspectives will be discussed.},
  language  = {en}
}