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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 The comparison of functional connectivity in Parkinson’s Disease patients with and without Parkin gene mutations(Turkish Neuropsychiatric Society, 2025-06-19) Çebi, Merve; Ay, Ulaş; Kıçik, Ani; Erdoğdu, Emel; Tepgeç, Fatih; Uyguner, Zehra Oya; Tüfekçioğlu, Zeynep; Samancı, Bedia; Bilgiç, Başar; Emre, Murat; Demiralp, Tamer; Hanağası, Haşmet AyhanIntroduction: Mapping the functional connectivity of brain regions became appealing in recent research in neurology. Accordingly, a growing body of evidence shows resting-state functional connectivity (rsFC) changes in neurodegenerative disorders including Parkinson’s Disease (PD). As characterised by extensive and progressive dopaminergic loss in the substantia nigra, PD emerges with serious motor and non-motor dysfunctions. In the literature, the minority of PD cases have been associated with certain genetic mutations. The aim of this study was to investigate the rsFC in a group of PD patients having Parkin gene mutation. Method: Twelve PD patients with Parkin mutation (PP-PD), 12 PD patients without Parkin mutation (PN-PD) and 12 healthy controls (HC) were included in the study. All participants underwent a resting-state functional magnetic resonance imaging as well as a neuropsychological assessment and clinical examination. Results: Results indicated that PP-PD had longer disease duration, a higher rate of dyskinesia and lower scores on complex visual perception tests. The resting state networks showed that all PD (consisting of PP-PD and PN-PD) and PP-PD groups had increased functional connectivity in the frontoparietal network as compared to the HC. In addition, the PP-PD group displayed decreased functional connectivity in the dorsal attention network compared to the PN-PD. Conclusion: In conclusion, our data suggests that PD with Parkin gene mutation might be emerging with distinct resting state functional connectivity changes in the brain.Yayın Investigation of symptom-specific functional connectivity patterns in Parkinson’s disease(Springer-Verlag Italia S.R.L., 2025-06-14) Kıçik, Ani; Bayram, Ali; Erdoğdu, Emel; Kurt, Elif; Sarıdede, Dilek Betül; Cengiz, Sevim; Bilgiç, Başar; Hanağası, Haşmet; Öztürk Işık, Esin; Gürvit, Hakan; Tüzün, Erdem; Demiralp, TamerParkinson’s disease (PD) is a complex neurodegenerative disease, characterized by pronounced heterogeneity in symptoms. This study investigates the functional connectivity (FC) patterns associated with distinct symptom clusters, aiming to elucidate the heterogeneity in PD and uncover the neural mechanisms underlying its motor and cognitive symptoms. Resting-state functional MRI (rs-fMRI) data from 55 non-demented PD patients and 24 healthy controls (HC) were used to perform seed-to-seed FC analyses. A clustering algorithm was applied to the cognitive and motor scores of all PD patients to generate relatively homogeneous symptomatic subgroups. PD patients exhibited a general decrease in FC within a network comprising the sensorimotor network (SMN) and the visual network (VN) regions. Symptom-based clustering revealed three relatively homogeneous subgroups, exhibiting a gradient pattern: patients with greater motor deficits showed significant disconnection within the SMN, whereas patients with greater visuospatial deficits exhibited reduced FC in an extended subnetwork, with pronounced disconnections between the VN and SMN areas. Our study demonstrated a notable disconnection between the SMN and VN, indicating impaired visual-motor integration in PD. Stronger disconnection within the SMN was associated with greater motor dysfunction, and stronger visual-sensorimotor disconnections were associated with greater visuospatial deficits. These findings suggest that at least two separate routes of functional disconnection may be responsible for the inhomogeneous symptom distribution in PD.
