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Education and Genetic Risk Modulate Hippocampal Structure in Alzheimer ’ s Disease

View Article: PubMed Central - PubMed

ABSTRACT

Genetic and environmental protective factors and risks modulate brain structure and function in neurodegenerative diseases and their preclinical stages. We wanted to investigate whether the years of formal education, a proxy measure for cognitive reserve, would influence hippocampal structure in Alzheimer’s disease patients, and whether apolipoprotein Eε4 (APOE4) carrier status and a first-degree family history of the disease would change a possible association. Fifty-eight Alzheimer’s disease patients underwent 3T magnetic resonance imaging. We applied a cortical unfolding approach to investigate individual subregions of the medial temporal lobe. Among patients homozygous for the APOE4 genotype or carrying both APOE4 and family history risks, lower education was associated with a thinner cortex in multiple medial temporal regions, including the hippocampus. Our data suggest that the years of formal education and genetic risks interact in their influence on hippocampal structure in Alzheimer’s disease patients.

No MeSH data available.


Cortical unfolding. After oblique coronal MRI scanning and manual segmentation of white matter and CSF on the T2 weighted MRI sequence, the resulting gray matter volume is computationally unfolded and flattened based on metric multidimensional scaling [right hemispheric flatmap shown, B]. Boundaries between the subregions are delineated on the original high-resolution MRI sequence (A) and later mathematically projected to flat map space. CA23DG=cornu ammonis fields 2,3 and dentate gyrus (the anterior part of the cornu ammonis fields and dentate gyrus [ant. CADG] is part of the CA23DG region), CA1=CA field 1, SUB=subiculum, ERC=entorhinal cortex, PRC=perirhinal cortex, PHC=parahippocampal cortex, FUS=fusiform cortex (fusiform boundary depicts the medial fusiform vertex).
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F1-ad-7-5-553: Cortical unfolding. After oblique coronal MRI scanning and manual segmentation of white matter and CSF on the T2 weighted MRI sequence, the resulting gray matter volume is computationally unfolded and flattened based on metric multidimensional scaling [right hemispheric flatmap shown, B]. Boundaries between the subregions are delineated on the original high-resolution MRI sequence (A) and later mathematically projected to flat map space. CA23DG=cornu ammonis fields 2,3 and dentate gyrus (the anterior part of the cornu ammonis fields and dentate gyrus [ant. CADG] is part of the CA23DG region), CA1=CA field 1, SUB=subiculum, ERC=entorhinal cortex, PRC=perirhinal cortex, PHC=parahippocampal cortex, FUS=fusiform cortex (fusiform boundary depicts the medial fusiform vertex).

Mentions: MRI scanning was performed on a GE Signa HDxt (General Electric Health Care, Waukesha, Wisconsin) 3T whole brain MRI scanner. We acquired a high-resolution oblique coronal T2 weighted fast spin echo sequence [repetition time 5200ms, echo time 105ms, slice thickness 3mm, spacing 0mm, 19 slices, in-plane voxel size 0.39 x 0.39 mm, field of view 200mm], and performed a detailed analysis of hippocampal and medial temporal lobe subregions by utilizing a cortical unfolding approach [22, 25, 26]. This technique enhances the visibility of the small and convoluted structures by flattening the region’s gray matter into two-dimensional space (Figure 1). Using MRI data with very high in-plane resolution, white matter and cerebrospinal fluid are manually defined (masked) in a fist step of the procedure. Labelling pixels as white matter or cerebrospinal fluid is performed with mrGray software [27] based on changes in signal intensity values. After this segmentation, the images (white matter and cerebrospinal fluid masks, resulting gray matter) are interpolated by a factor of 7 to achieve nearly isotropic voxels of approx. 0.4mm3. The entire gray matter volume is then grown out in connected layers using a region-expansion algorithm, containing cornu ammonis (CA) fields 1-3 and the dentate gyrus, subiculum, entorhinal, perirhinal, and parahippocampal cortices, and the fusiform gyrus. After the computational unfolding, which is based on metric multidimensional scaling, boundaries between subfields are mathematically projected to their flat map space coordinates after their delineation on the original MRI sequence using histological and MRI atlases [28, 29]. The accuracy of the cortical unfolding technique has been previously demonstrated in different studies [17, 22, 25]. The cortical thickness of all subregions is calculated in three-dimensional space. For each gray matter voxel, the distance to the closest non-gray matter voxel is computed. In two-dimensional space, for each voxel, the maximum distance value of the corresponding three-dimensional voxels across all layers is taken and multiplied by two. Thickness in each subregion is calculated by averaging the thickness of all two-dimensional voxels. For technological details of the cortical unfolding technique see [25, 26] as well as [17] for cortical thickness measurements. In line with our previous studies applying cortical unfolding we report raw (uncorrected) data, which is the preferred strategy for investigating cortical thickness in contrast to volume [30]. Investigators performing segmentations and cortical unfolding were unaware of the patients’ clinical or demographic characteristics.


Education and Genetic Risk Modulate Hippocampal Structure in Alzheimer ’ s Disease
Cortical unfolding. After oblique coronal MRI scanning and manual segmentation of white matter and CSF on the T2 weighted MRI sequence, the resulting gray matter volume is computationally unfolded and flattened based on metric multidimensional scaling [right hemispheric flatmap shown, B]. Boundaries between the subregions are delineated on the original high-resolution MRI sequence (A) and later mathematically projected to flat map space. CA23DG=cornu ammonis fields 2,3 and dentate gyrus (the anterior part of the cornu ammonis fields and dentate gyrus [ant. CADG] is part of the CA23DG region), CA1=CA field 1, SUB=subiculum, ERC=entorhinal cortex, PRC=perirhinal cortex, PHC=parahippocampal cortex, FUS=fusiform cortex (fusiform boundary depicts the medial fusiform vertex).
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Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC5036951&req=5

F1-ad-7-5-553: Cortical unfolding. After oblique coronal MRI scanning and manual segmentation of white matter and CSF on the T2 weighted MRI sequence, the resulting gray matter volume is computationally unfolded and flattened based on metric multidimensional scaling [right hemispheric flatmap shown, B]. Boundaries between the subregions are delineated on the original high-resolution MRI sequence (A) and later mathematically projected to flat map space. CA23DG=cornu ammonis fields 2,3 and dentate gyrus (the anterior part of the cornu ammonis fields and dentate gyrus [ant. CADG] is part of the CA23DG region), CA1=CA field 1, SUB=subiculum, ERC=entorhinal cortex, PRC=perirhinal cortex, PHC=parahippocampal cortex, FUS=fusiform cortex (fusiform boundary depicts the medial fusiform vertex).
Mentions: MRI scanning was performed on a GE Signa HDxt (General Electric Health Care, Waukesha, Wisconsin) 3T whole brain MRI scanner. We acquired a high-resolution oblique coronal T2 weighted fast spin echo sequence [repetition time 5200ms, echo time 105ms, slice thickness 3mm, spacing 0mm, 19 slices, in-plane voxel size 0.39 x 0.39 mm, field of view 200mm], and performed a detailed analysis of hippocampal and medial temporal lobe subregions by utilizing a cortical unfolding approach [22, 25, 26]. This technique enhances the visibility of the small and convoluted structures by flattening the region’s gray matter into two-dimensional space (Figure 1). Using MRI data with very high in-plane resolution, white matter and cerebrospinal fluid are manually defined (masked) in a fist step of the procedure. Labelling pixels as white matter or cerebrospinal fluid is performed with mrGray software [27] based on changes in signal intensity values. After this segmentation, the images (white matter and cerebrospinal fluid masks, resulting gray matter) are interpolated by a factor of 7 to achieve nearly isotropic voxels of approx. 0.4mm3. The entire gray matter volume is then grown out in connected layers using a region-expansion algorithm, containing cornu ammonis (CA) fields 1-3 and the dentate gyrus, subiculum, entorhinal, perirhinal, and parahippocampal cortices, and the fusiform gyrus. After the computational unfolding, which is based on metric multidimensional scaling, boundaries between subfields are mathematically projected to their flat map space coordinates after their delineation on the original MRI sequence using histological and MRI atlases [28, 29]. The accuracy of the cortical unfolding technique has been previously demonstrated in different studies [17, 22, 25]. The cortical thickness of all subregions is calculated in three-dimensional space. For each gray matter voxel, the distance to the closest non-gray matter voxel is computed. In two-dimensional space, for each voxel, the maximum distance value of the corresponding three-dimensional voxels across all layers is taken and multiplied by two. Thickness in each subregion is calculated by averaging the thickness of all two-dimensional voxels. For technological details of the cortical unfolding technique see [25, 26] as well as [17] for cortical thickness measurements. In line with our previous studies applying cortical unfolding we report raw (uncorrected) data, which is the preferred strategy for investigating cortical thickness in contrast to volume [30]. Investigators performing segmentations and cortical unfolding were unaware of the patients’ clinical or demographic characteristics.

View Article: PubMed Central - PubMed

ABSTRACT

Genetic and environmental protective factors and risks modulate brain structure and function in neurodegenerative diseases and their preclinical stages. We wanted to investigate whether the years of formal education, a proxy measure for cognitive reserve, would influence hippocampal structure in Alzheimer’s disease patients, and whether apolipoprotein Eε4 (APOE4) carrier status and a first-degree family history of the disease would change a possible association. Fifty-eight Alzheimer’s disease patients underwent 3T magnetic resonance imaging. We applied a cortical unfolding approach to investigate individual subregions of the medial temporal lobe. Among patients homozygous for the APOE4 genotype or carrying both APOE4 and family history risks, lower education was associated with a thinner cortex in multiple medial temporal regions, including the hippocampus. Our data suggest that the years of formal education and genetic risks interact in their influence on hippocampal structure in Alzheimer’s disease patients.

No MeSH data available.