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Yayın Identification of metabolic correlates of mild cognitive impairment in Parkinson's disease using magnetic resonance spectroscopic imaging and machine learning(Springer Science and Business Media Deutschland GmbH, 2022-12) Cengiz, Sevim; Arslan, Dilek Betül; Kıçik, Ani; Erdoğdu, Emel; Yıldırım, Muhammed; Hatay, Gökçe Hale; Tüfekçioğlu, Zeynep; Uluğ, Aziz Müfit; Bilgiç, Başar; Hanagasi, Haşmet; Demiralp, Tamer; Gürvit, Hakan; Öztürk Işıkk, EsinObjective: To investigate metabolic changes of mild cognitive impairment in Parkinson’s disease (PD-MCI) using proton magnetic resonance spectroscopic imaging (1H-MRSI). Methods: Sixteen healthy controls (HC), 26 cognitively normal Parkinson’s disease (PD-CN) patients, and 34 PD-MCI patients were scanned in this prospective study. Neuropsychological tests were performed, and three-dimensional 1H-MRSI was obtained at 3 T. Metabolic parameters and neuropsychological test scores were compared between PD-MCI, PD-CN, and HC. The correlations between neuropsychological test scores and metabolic intensities were also assessed. Supervised machine learning algorithms were applied to classify HC, PD-CN, and PD-MCI groups based on metabolite levels. Results: PD-MCI had a lower corrected total N-acetylaspartate over total creatine ratio (tNAA/tCr) in the right precentral gyrus, corresponding to the sensorimotor network (p = 0.01), and a lower tNAA over myoinositol ratio (tNAA/mI) at a part of the default mode network, corresponding to the retrosplenial cortex (p = 0.04) than PD-CN. The HC and PD-MCI patients were classified with an accuracy of 86.4% (sensitivity = 72.7% and specificity = 81.8%) using bagged trees. Conclusion: 1H-MRSI revealed metabolic changes in the default mode, ventral attention/salience, and sensorimotor networks of PD-MCI patients, which could be summarized mainly as ‘posterior cortical metabolic changes’ related with cognitive dysfunction.Yayın An investigation of affective personality traits in Alzheimer’s disease: seeking as a possible predictor for early-stage Alzheimer’s dementia(Routledge, 2023-09) Soncu Büyükişcan, Ezgi; Yıldırım, Elif; Demirtaş Tatlıdede, Aslı; Bilgiç, Başar; Gürvit, HakanObjective: The aim of the current study was to investigate affective personality traits in Alzheimer’s disease, a neurodegenerative condition mainly characterized by episodic memory impairment. Method: The sample included 69 participants from 3 diagnostic categories. Twenty-five participants were diagnosed with subjective cognitive impairment (SCI), 26 participants were diagnosed with mild cognitive impairment of the amnestic type (aMCI), and the remaining 18 participants were diagnosed with early-stage Alzheimer’s dementia (ADD). Diagnostic labels were given as a result of detailed neurological, neuropsychological, and neuroradiological assessment. Affective personality traits were assessed via Affective Neuroscience Personality Scales (ANPS). Results: The only significant intergroup difference was obtained for the SEEKING subscale of ANPS. Here, ADD group scored significantly lower compared to the SCI group. The results of logistic regression analysis also indicated that SEEKING score successfully predicted early-stage ADD diagnosis. Conclusion: The results suggest that a specific personality constellation characterized by reduced investment in the outside world might be associated with Alzheimer’s disease, either as a risk factor or a byproduct of the neurodegenerative process initiated by AD pathology.
