Despite heightened risk of cognitive decline, no evidence of local atrophy in people with subjective cognitive decline compared to normal controls in ADNI. (1st February 2022)

• Record Type: Journal Article
• Authors: Morrison, Cassandra; Dadar, Mahsa; Shafiee, Neda; Collins, Louis
• Is Part Of: Alzheimer's & dementia. Volume 17(2021)Supplement 4
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-02-01
• 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.054475
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: People with subjective cognitive decline (SCD) are at increased risk for developing Alzheimer's disease (AD). SCD may thus be a very early clinical manifestations of AD. However, identifying which individuals with SCD will develop AD is difficult with current biomarker techniques. To predict whether someone with SCD will progress to AD, it is necessary to determine whether people with SCD display neurodegeneration in brain regions associated with AD. Method: We included 1769 baseline and follow‐up MRI scans for 447 participants (177 normal controls, NC; 100 SCD; and 170 early mild cognitive impairment, eMCI) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). All scans were pre‐processed through a previously validated pipeline. Deformation‐based morphometry (DBM) was performed to examine the pattern of volumetric change over time. An atlas‐based approach was also used to examine mean volume differences for regions of interest (ROIs; lateral ventricles, entorhinal cortex, and amygdala from CerebrA atlas (Manera et al., 2020)) estimated by integrating the Jacobian of the deformation field within the ROI. A previously validated MRI analysis method (SNIPE) was used to determine volume and grading of the hippocampus (Coupe et al., 2012). We applied a linear mixed effects model for all analysis ( volume ∼Diagnostic Group +Age +Sex +Amyloid Positivity +APOE e4 +Education +1|ID ). Result: Longitudinal volume analysis showed slight atrophy in eMCI compared to NC and SCD. ROI analysis revealed that eMCI had smaller volumes than SCD and NC in the amygdala (NC & SCD: p <.001) and entorhinal cortex (NC: p <.001; SCD: p =.01), and larger lateral ventricles (NC & SCD: p =.01). SNIPE volume and grading analysis revealed that eMCI hippocampal volume differed from both NC and SCD ( p <.001). SCD and NC did not differ in any of the analyses. With respect to demographics, people with SCD had 2 years more education ( p <0.001) than eMCI and NC. Conclusion: The structural differences observed in eMCI may act as an early biomarker for AD. Although SCD participants' brain volumes significantly differed from eMCI, they did not differ from NC. However, lack of SCD:NC differences may be due to confounds (e.g., greater education in SCD) within the sample.