Publications by authors named "A L Ziengs"

Background: Neurocognitive impairment is common in kidney transplant recipients (KTRs). Adequate brain functioning requires energy and neurotransmitter activity, for which iron is essential. We aimed to investigate iron deficiency (ID) as a potentially modifiable risk factor for cognitive impairment in KTRs.

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Background: Emerging data suggest that erythropoietin (EPO) promotes neural plasticity and that iron homeostasis is needed to maintain normal physiological brain function. Cognitive functioning could therefore be influenced by endogenous EPO levels and disturbances in iron status.

Objective: To determine whether endogenous EPO levels and disturbances in iron status are associated with alterations in cognitive functioning in the general population.

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Background: Cognitive impairment is often present shortly after transplantation in kidney transplant recipients (KTR). To date, it is unknown whether these impairments persist in thelong term, to what extent they are associated with disease-related variables and whether they affect societal participation and quality of life (QoL) of KTR.

Method: This study was part of the TransplantLines Biobank & Cohort Study in the University Medical Center Groningen.

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Introduction: In the past decades, short-term results after solid organ transplantation have markedly improved. Disappointingly, this has not been accompanied by parallel improvements in long-term outcomes after transplantation. To improve graft and recipient outcomes, identification of potentially modifiable risk factors and development of biomarkers are required.

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Introduction: We aimed to uncover the pattern of network-level changes in neuronal function in Spinocerebellar ataxia type 3 (SCA3).

Methods: 17 genetically-confirmed SCA3 patients and 16 controls underwent structural MRI and static resting-state [F]‑Fluoro‑deoxyglucose Positron Emission Tomography (FDG-PET) imaging. A SCA3-related pattern (SCA3-RP) was identified using a multivariate method (scaled subprofile model and principal component analysis (SSM PCA)).

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