Associations between iron deposition in the brain and grey matter volumes in cognitively unimpaired adults. (31st December 2021)

• Record Type: Journal Article
• Authors: Stankeviciute, Laura; Falcon, Carles; Operto, Grégory; Rojas, Santiago; Grau‐Rivera, Oriol; Garcia, Marina; Minguillón, Carolina; Fauria, Karine; Molinuevo, Jose; Zetterberg, Henrik; Blennow, Kaj; Suarez‐Calvet, Marc; Cacciaglia, Raffaele; Gispert, Juan Domingo
• Is Part Of: Alzheimer's & dementia. Volume 17(2021)Supplement 5
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-12-31
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.058103
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Iron dyshomeostasis is involved in the pathophysiology of Alzheimer's disease (AD). Magnetic resonance imaging (MRI) is sensitive to iron in the brain as its concentration decreases the intensity of T2‐weighted images. However, there is little evidence on how iron affects structural changes in the brain of cognitively unimpaired individuals at the inception of the Alzheimer's continuum . This research aimed to investigate the relationship between T2 MR hypointensities, as a proxy for iron content, and grey matter volume (GMv) in middle‐aged cognitively unimpaired (CU) individuals. Methods: This cross‐sectional study included 302 CU adults from the ALFA+ cohort who underwent MRI, cerebrospinal fluid sampling (CSF) and neuropsychological assessment (Table 1). T2‐weighted images were used to calculate mean hypointensity values in a set of 18 subcortical nuclei (http://nist.mni.mcgill.ca/?p=1209 ). T1w scans were entered into voxel‐based morphometry (VBM) analysis to evaluate the relationship between regional T2 intensities and GM volumes. Due to the strong correlations between the T2 intensity of the subcortical regions, we performed principal component analysis (PCA) to reduce the dimensionality (Table 2). We created a general linear model where GMv was the dependent variable, the first principal component (PC1) was the independent variable and age, sex, APOE ‐ε4 status, education level and total intracranial volume (TIV) were the covariates. In an additional model, CSF levels of amyloid‐beta (Aβ) ratio (CSF Aβ42/40) and phosphorylated tau (p‐tau) were entered as covariates. Statistical significance was set at p<0.001 uncorrected for multiple comparisons with a cluster‐level threshold of 100. Results: PC1 explained 47.64% of the variance, and it was significantly and negatively associated with grey matter volumes in a highly symmetrical pattern which included the parahippocampal cortex (Table 3. Figure 1). These results remained largely unchanged when entering CSF AD biomarkers in the model. Conclusions: Our results indicate that, in cognitively unimpaired individuals, a higher content of iron deposition, as expressed by lower T2‐weighted MR intensities in subcortical regions, are associated with higher grey matter volumes in parahippocampus, independently of CSF AD biomarkers. These preliminary results may suggest that iron accumulation might be associated with neuroinflammatory mechanisms and render the brain more vulnerable to early AD pathology.