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Sökning: WFRF:(Poulakis K.)

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  • Inguanzo, A, et al. (författare)
  • MRI data-driven clustering reveals different subtypes of Dementia with Lewy bodies
  • 2023
  • Ingår i: NPJ Parkinson's disease. - : Springer Science and Business Media LLC. - 2373-8057. ; 9:1, s. 5-
  • Tidskriftsartikel (refereegranskat)abstract
    • Dementia with Lewy bodies (DLB) is a neurodegenerative disorder with a wide heterogeneity of symptoms, which suggests the existence of different subtypes. We used data-driven analysis of magnetic resonance imaging (MRI) data to investigate DLB subtypes. We included 165 DLB from the Mayo Clinic and 3 centers from the European DLB consortium and performed a hierarchical cluster analysis to identify subtypes based on gray matter (GM) volumes. To characterize the subtypes, we used demographic and clinical data, as well as β-amyloid, tau, and cerebrovascular biomarkers at baseline, and cognitive decline over three years. We identified 3 subtypes: an older subtype with reduced cortical GM volumes, worse cognition, and faster cognitive decline (n = 49, 30%); a subtype with low GM volumes in fronto-occipital regions (n = 76, 46%); and a subtype of younger patients with the highest cortical GM volumes, proportionally lower GM volumes in basal ganglia and the highest frequency of cognitive fluctuations (n = 40, 24%). This study shows the existence of MRI subtypes in DLB, which may have implications for clinical workout, research, and therapeutic decisions.
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  • Albrecht, F., et al. (författare)
  • Unraveling Parkinson's disease heterogeneity using subtypes based on multimodal data
  • 2022
  • Ingår i: Parkinsonism and Related Disorders. - : Elsevier BV. - 1353-8020 .- 1873-5126. ; 102, s. 19-29
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Parkinson's disease (PD) is a clinically and neuroanatomically heterogeneous neurodegenerative disease characterized by different subtypes. To this date, no studies have used multimodal data that combines clinical, motor, cognitive and neuroimaging assessments to identify these subtypes, which may provide complementary, clinically relevant information. To address this limitation, we subtyped participants with mild-moderate PD based on a rich, multimodal dataset of clinical, cognitive, motor, and neuroimaging variables. Methods: Cross-sectional data from 95 PD participants from our randomized EXPANd (EXercise in PArkinson's disease and Neuroplasticity) controlled trial were included. Participants were subtyped using clinical, motor, and cognitive assessments as well as structural and resting-state MRI data. Subtyping was done by random forest clustering. We extracted information about the subtypes by inspecting their neuroimaging profiles and descriptive statistics. Results: Our multimodal subtyping analysis yielded three PD subtypes: a motor-cognitive subtype characterized by widespread alterations in brain structure and function as well as impairment in motor and cognitive abilities; a cognitive dominant subtype mainly impaired in cognitive function that showed frontoparietal structural and functional changes; and a motor dominant subtype impaired in motor variables without any brain alterations. Motor variables were most important for the subtyping, followed by gray matter volume in the right medial postcentral gyrus. Conclusions: Three distinct PD subtypes were identified in our multimodal dataset. The most important features to subtype PD participants were motor variables in addition to structural MRI in the sensorimotor region. These findings have the potential to improve our understanding of PD heterogeneity, which in turn can lead to personalized interventions and rehabilitation.
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  • Badji, A., et al. (författare)
  • Cerebrospinal Fluid Biomarkers, Brain Structural and Cognitive Performances Between Normotensive and Hypertensive Controlled, Uncontrolled and Untreated 70-Year-Old Adults
  • 2022
  • Ingår i: Frontiers in Aging Neuroscience. - : Frontiers Media SA. - 1663-4365. ; 13
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Hypertension is an important risk factor for Alzheimer's disease (AD). The pathophysiological mechanisms underlying the relationship between AD and hypertension are not fully understood, but they most likely involve microvascular dysfunction and cerebrovascular pathology. Although previous studies have assessed the impact of hypertension on different markers of brain integrity, no study has yet provided a comprehensive comparison of cerebrospinal fluid (CSF) biomarkers and structural brain differences between normotensive and hypertensive groups in a single and large cohort of older adults in relationship to cognitive performances.Objective: The aim of the present work was to investigate the differences in cognitive performances, CSF biomarkers and magnetic resonance imaging (MRI) of brain structure between normotensive, controlled hypertensive, uncontrolled hypertensive, and untreated hypertensive older adults from the Gothenburg H70 Birth Cohort Studies.Methods: As an indicator of vascular brain pathology, we measured white matter hyperintensities (WMHs), lacunes, cerebral microbleeds, enlarged perivascular space (epvs), and fractional anisotropy (FA). To assess markers of AD pathology/neurodegeneration, we measured hippocampal volume, temporal cortical thickness on MRI, and amyloid-beta(42), phosphorylated tau, and neurofilament light protein (NfL) in cerebrospinal fluid. Various neuropsychological tests were used to assess performances in memory, attention/processing speed, executive function, verbal fluency, and visuospatial abilities.Results: We found more white matter pathology in hypertensive compared to normotensive participants, with the highest vascular burden in uncontrolled participants (e.g., lower FA, more WMHs, and epvs). No significant difference was found in any MRI or CSF markers of AD pathology/neurodegeneration when comparing normotensive and hypertensive participants, nor among hypertensive groups. No significant difference was found in most cognitive functions between groups.Conclusion: Our results suggest that good blood pressure control may help prevent cerebrovascular pathology. In addition, hypertension may contribute to cognitive decline through its effect on cerebrovascular pathology rather than AD-related pathology. These findings suggest that hypertension is associated with MRI markers of vascular pathology in the absence of a significant decline in cognitive functions.
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  • Cedres, N, et al. (författare)
  • Brain Atrophy Subtypes and the ATN Classification Scheme in Alzheimer's Disease
  • 2021
  • Ingår i: Neuro-degenerative diseases. - : S. Karger AG. - 1660-2862 .- 1660-2854. ; 20:4, s. 153-164
  • Tidskriftsartikel (refereegranskat)abstract
    • <b><i>Introduction:</i></b> We investigated the association between atrophy subtypes of Alzheimer’s disease (AD), the ATN classification scheme, and key demographic and clinical factors in 2 cohorts with different source characteristics (a highly selective research-oriented cohort, the Alzheimer’s Disease Neuroimaging Initiative [ADNI]; and a naturalistic heterogeneous clinically oriented cohort, Karolinska Imaging Dementia Study [KIDS]). <b><i>Methods:</i></b> A total of 382 AD patients were included. Factorial analysis of mixed data was used to investigate associations between AD subtypes based on brain atrophy patterns, ATN profiles based on cerebrospinal fluid biomarkers, and age, sex, Mini Mental State Examination (MMSE), cerebrovascular disease (burden of white matter signal abnormalities, WMSAs), and <i>APOE</i> genotype. <b><i>Results:</i></b> Older patients with high WMSA burden, belonging to the typical AD subtype and showing A+T+N+ or A+T+N− profiles clustered together and were mainly from ADNI. Younger patients with low WMSA burden, limbic-predominant or minimal atrophy AD subtypes, and A+T−N− or A+T−N+ profiles clustered together and were mainly from KIDS. <i>APOE</i> ε4 carriers more frequently showed the A+T−N− and A+T+N− profiles. <b><i>Conclusions:</i></b> Our findings align with the recent framework for biological subtypes of AD: the combination of risk factors, protective factors, and brain pathologies determines belonging of AD patients to distinct subtypes.
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